Keywords: Visual Navigation, Recognition, Mapping
Abstract: In order to diminish the influence of pose choice during appearance-based mapping, a more natural representation of location models is established using covisibility graphs. As the robot moves through the environment, visual landmarks are detected, and connected if seen as covisible. The introduction of a novel generative model allows relevant subgraphs of the covisibility map to be compared to a given query without needing to normalize over all previously seen locations. The use of probabilistic methods provides a unified framework to incorporate sensor error, perceptual aliasing, decision thresholds, and multiple location matches. The system is evaluated and compared with other state-of-the-art methods.

Keywords: Visual Navigation, SLAM, Computer Vision
Abstract: This work is concerned with the matching of straight lines between two stereo image pairs by reprojection. While we will focus on visual odometry in the realm of simultaneous mapping and localization, the techniques are also relevant to monocular and stereo 3D object detection and tracking. Our first contribution is an adaptation of the Iterative Closest Point (ICP) algorithm to the domain of lines. We argue that a naive "Iterative Closest Line" derivation cannot deliver similar performance. In contrast, our novel Iterative Closest Multiple Lines (ICML) algorithm allows efficient line matching while even reducing the amount of local minima during iterative optimization with its consideration of several weighted matches. The second contribution is a fast and robust hypothesize-and-test algorithm which can act as a fallback for challenging frame pairs where pure gradient-based optimization fails. In several differently textured scenes, we demonstrate robust performance, even in very sparse cases where proven feature point based methods fail. In comparison to edge-point ICP, we see speed improvements of more than an order of a magnitude and reduced susceptibility for local minima.

Keywords: Localization, Sensor Fusion, Computer Vision
Abstract: We present a new matching algorithm considering a priori (the prior probability) based on Bayes' theorem. Performance of point cloud registration between target and source clouds is effectively improved by introducing maximum a posteriori (MAP) estimation. The standard Iterative Closest Point (ICP) algorithm for the registration sometimes falls into misalignment due to measurement errors, narrow sensing field of view, or the movement of objects during measurement. Our approach resolves such problems by considering both the likelihood of the measurement and the prior probability of the initial guess for registration in the objective function. We have implemented a new 6DOF Iterative Closest Point matching using MAP estimation, and evaluated the method in real environments comparing with conventional registration methods. The experimental results have shown that our proposed method has wide convergence region and matches point clouds accurately preventing the misalignment problem.

Keywords: Visual Navigation, Sensor Fusion, Unmanned Aerial Systems
Abstract: In this paper, we describe a novel approach in fusing optical flow with inertial cues (3D acceleration and 3D angular velocities) in order to navigate a Micro Aerial Vehicle (MAV) drift free in 4DoF and metric velocity. Our approach only requires two consecutive images with a minimum of three feature matches. It does not require any (point) map nor any type of feature history. Thus it is an inherently failsafe approach that is immune to map and feature-track failures. With these minimal requirements we show in real experiments that the system is able to navigate drift free in all angles including yaw, in one metric position axis, and in 3D metric velocity. Furthermore, it is a power-on-and-go system able to online self-calibrate the inertial biases, the visual scale and the full 6DoF extrinsic transformation parameters between camera and IMU.

Keywords: Visual Navigation, Calibration and Identification, Sensor Fusion
Abstract: In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point feature are considered as state variables. In particular, we prove that the system has only three unobservable directions orresponding to global translations along the x and y axes, and rotations around the gravity vector. Hence, compared to general VINS, an advantage of using only ground features is that the vertical translation becomes observable. The findings of the theoretical analysis are validated through real-world experiments.

Keywords: Recognition, Range Sensing, Computer Vision
Abstract: In this paper, we propose a segment-based object detection approach using laser range data. Our detection approach is built up of three stages: First, a hierarchical segmentation approach generates a hierarchy of coarse-to-fine segments to reduce the impact of over- and under-segmentation in later stages. Next, we employ a learned mixture model to classify all segments. The model combines multiple softmax regression classifiers learned on specific bag-of-word representations using different parameterizations of a descriptor. In the final stage, we filter irrelevant and duplicate detections using a greedy method in consideration of the segment hierarchy. We experimentally evaluate our approach on recently published real-world datasets to detect pedestrians, cars, and cyclists.

Attachments: Video Attachment
Keywords: Visual Tracking, Human detection and tracking, Computer Vision
Abstract: Tracking multiple moving targets in video is still a challenge because of mutual occlusion problem. This paper presents a Gaussian mixture probability hypothesis density-based visual tracking system with game theory-based mutual occlusion handling. First, a two-step occlusion reasoning algorithm is proposed to determine the occlusion region. Then, the spatial constraint-based appearance model with other interacting targets’ interferences is modeled. Finally, an n-person, non-zero-sum, non-cooperative game is constructed to handle the mutual occlusion problem. The individual measurements within the occlusion region are regarded as the players in the constructed game competing for the maximum utilities by using the certain strategies. The Nash Equilibrium of the game is the optimal estimation of the locations of the players within the occlusion region. Experiments conducted on publicly available videos demonstrate the good performance of the proposed occlusion handling algorithm.

Attachments: Video Attachment
Keywords: Computer Vision, Mapping, Service Robots
Abstract: In this paper, we present a novel method for surface reconstruction with a low execution time for segmenting and representing scattered scenes accurately. The surfaces are described in a memory-efficient fashion as polynomial functions and polygons. Segmentation and parameter determination is done in one pass by using a quadtree on ordered point clouds, which results in a complexity of O(log n).

This paper includes an evaluation with respect to reconstruction accuracy, segmentation precision, execution time and compression ratio of everyday indoor scenes. Our surface reconstruction algorithm outperforms comparable approaches with respect to execution time and accuracy. More importantly, the new technique handles curved shapes accurately and enables complex tasks like 3D mapping for mobile robots in an unknown environment.

Keywords: Biologically-Inspired Robots, Computer Vision
Abstract: This paper introduces a new time oriented visual feature extraction method developed to take full advantage of an asynchronous event-based camera. Event-based asynchronous cameras encode visual information in an extremely optimal manner in term of redundancy reduction and energy consumption. These sensors open vast perspectives in the field of mobile robotics where responsiveness is one of the most important needed property. The presented technique, based on echo-state networks will be shown particularly suited for unsupervised features extraction in the context of high dynamic environments. Experimental results are presented, they show the method adequacy with the high data sparseness and temporal resolution of event-based acquisition. This allows features extraction at millisecond accuracy with a low computational cost.

Keywords: Computer Vision, Visual Navigation, Sensor Fusion
Abstract: Efficient visual pose estimation plays an important role for a variety of applications. To improve the quality, the measurements from different sensors can be fused. However, a reliable fusion requires the knowledge of the uncertainty of each estimate. In this work, we provide an error analysis for the Zinf algorithm. Furthermore, we extend the existing first-order error propagation for the 8-point algorithm to allow for feature normalization, as proposed by Hartley or Mühlich, and the rotation matrix based decomposition. Both methods are efficient visual odometry techniques which allow high frame-rates and, thus, dynamic motions in unbounded workspaces. Finally, we provide experiments which validate the accuracy of the error propagation and which enable a brief comparison, showing that the Zinf significantly outperforms the 8-point algorithm. We also discuss the influence of the number of features, the aperture angle, and the image resolution on the accuracy of the pose estimation.

Keywords: Computer Vision, Recognition, Visual Learning
Abstract: This paper presents a method for finding the largest, connected, smooth surface in noisy depth images. The formulation of the fitting in a Sample Consensus way allows the use of RANSAC or any other similar estimator, and makes the method tolerant to low percentage of inliers in the input. Therefore it can be used to simmultaneously segment and model the surface of interest. This is important in applications like analyzing physical properties of Carbon-fiber-reinforced polymer (CFRP) structures. Using bivariate polynomials for modeling turns out to be advantageous, allowing to capture the variations along the two directions on the surface. However, fitting them efficiently using RANSAC is not straightforward. We present the necessary preand post-processing, distance and normal direction checks, and degree optimization (lowering the order of the polynomial), and evaluate how these improve results. Finally, to improve the initial estimate provided by RANSAC, an Expectation Maximization approach is employed, converging to the best solution. The method was tested on high-quality data and as well as real-world scenes captured by an RGB-D camera. We will publish the method as part of the Point Cloud Library.

Keywords: Computer Vision, Localization, Sensor Fusion
Abstract: This paper provides two novel contributions. The former regards the observability of the visual-inertial structure from motion. It is proven that, the information contained in the data provided by a monocular camera which observes a single point-feature and by an Inertial Measurement Unit (IMU) allows estimating the absolute scale, the speed in the local frame, the absolute roll and pitch angles, the biases which affect the accelerometer's and the gyroscope's measurements, the magnitude of the gravitational acceleration and the extrinsic camera-IMU calibration. The latter contribution is the derivation of a new closed form solution to determine some of the previous observable quantities by only using few camera measurements collected during a short time interval and the data provided by the IMU during the same time interval. This closed-solution allows us to investigate the intrinsic properties of the visual-inertial structure from motion and in particular to identify the conditions under which the problem has a finite number of solutions. Specifically, it is shown that the problem can have a unique solution, two distinct solutions and infinite solutions depending on the trajectory, on the number of point-features and on their layout and on the number of camera images. The proposed closed solution is finally used in conjunction with a filter based approach in order to show its benefit.

Keywords: Rehabilitation Robotics, Medical Systems, Healthcare, and Assisted Living, Human-Robot Interaction
Abstract: Cerebral palsy (CP) is a disorder of movement and posture in children caused by non-progressive insult of the immature brain. The characteristic features are weakness, spasticity, muscle contractures, and poor motor coordination. The gait patterns of children with CP are slow, uncoordinated, and unstable. Our hypothesis is that these impaired children will benefit from robot enhanced walkers to improve their balance, coordination, and speed during gait. In addition, this experience will also impact their clinical scores that relate to their functional performance and caregiver assistance.

In this study, we used a specially-designed robotic walker which children used to perform a series of walking tasks, in increasing order of difficulty. This study was performed in 30 training sessions over a period of 3 months. Each training session lasted for 20 minutes. The outcome measures were variables recorded by the robot such as travel distance, average speed, and clinical measured variables that characterize their disability profiles.

Keywords: Medical Systems, Healthcare, and Assisted Living, Rehabilitation Robotics, Human Performance Augmentation
Abstract: Myoelectrical signals have many applications in medical, sports, wearable robotics and computing fields. Wet electrodes are widely used to acquire these signals. In contrast, dry contact electrodes and noncontact capacitive coupling electrodes have been developed. However, their use has several limitations. In this research, we developed a hybrid electrode that is capable of both capacitive and resistive recordings by optimizing the sensor input impedance value using a new electrode noise model that contained noise sources. We extend this design so that noise originated during real usage, such as motion artifacts and noise from electric motors is also measured and removed from the sensor output. In experiments, noise analysis and experiments were performed by measuring myoelectrical signals from both upper and lower limbs in realistic situations, including weight lifting, robot arm control, and walking on a treadmill. As the results, we verified that our electrodes were capable of bioelectrical measurements at noise levels comparable to wet electrodes in realistic situations and with high correlation coefficients between both types of sensors.

Keywords: Rehabilitation Robotics, Medical Systems, Healthcare, and Assisted Living, Haptics and Haptic Interfaces
Abstract: Supplementary visual, audio and tactile inputs have been shown to enhance postural control. In particular the light touch on a stable surface has been proven to significantly increase postural stability. Furthermore, it has been reported that the Center of Pressure (CoP) can be sinusoidally driven thanks to somatosensory inputs. In this paper, these results are extended to improve balance control. A closed loop control of the CoP based on somatosensory feedback is developed. This control strategy allows both set-point tracking and path following of the CoP. The effectiveness of the proposed somatosensory feedback is assessed through experiments involving 11~naive subjects.

Keywords: Medical Systems, Healthcare, and Assisted Living, Wheeled Robots, Human-Robot Interaction
Abstract: In this paper, a method to perform semi-autonomous navigation on a wheelchair is presented. The wheelchair could be controlled in semi-autonomous mode estimating the user's intention by using a face pose recognition system or in manual mode. The estimator was performed within a Bayesian network approach. To switch these two modes, a speech interface was used. The user's intention was modeled as a set of typical destinations visited by the user. The algorithm was implemented to one experimental wheelchair robot. The new application of the wheelchair system with more natural and easy-to-use human machine interfaces was one of the main contributions. as user's habits and points of interest are employed to infer the user's desired destination in a map. Erroneous steering signals coming from the user-machine interface input are filtered out, improving the overall performance of the system. Human aware navigation, path planning and obstacle avoidance are performed by the robotic wheelchair while the user is just concerned with ``looking where he wants to go''.

Attachments: Video Attachment
Keywords: Rehabilitation Robotics, Learning from Demonstration, Humanoid and Bipedal Locomotion
Abstract: Impedance control is a common framework for control of lower-limb prosthetic devices. This approach requires choosing many impedance controller parameters. In this paper, we show how to learn these parameters for lower-limb prostheses by observation of unimpaired human walkers. We validate our approach in simulation of a transfemoral amputee, and we demonstrate the performance of the learned parameters in a preliminary experiment with a lower-limb prosthetic device.

Keywords: Human Performance Augmentation, Smart Actuators, Micro-manipulation
Abstract: Involuntary motions of the hand can have a significant deteriorating effect on the performance of microsurgical procedures such as vitreoretinal microsurgery. The most common source of the involuntary motions is physiological tremor. Real-time compensation of physiological tremor is therefore necessary to assist surgeons to accurately perform a microsurgery. A novel approach based on the use of Ionic Polymer Metallic Composites (IPMCs) has been developed for actively compensating physiological tremor in the hand. We present the design of our novel handheld device that compensates for tremor using an IPMC-based actuator. We then experimentally evaluate the device to show the amount of compensation achieved.

Keywords: Animation and Simulation, Software and Architecture
Abstract: Three-dimensional, physics-based simulators are important to the field of self-reconfigurable robotics because they allow researchers to approximate the physical interactions and autonomous behaviors of large numbers of modules in a low-cost, safe, and highly-controlled manner. This paper presents a novel, high-performance, general-purpose simulator for autonomous, self-reconfigurable robots called ReMod3D (RM3D) that overcomes the speed and scalability limitations of existing self-reconfigurable simulators while, at the same time, allowing for realistic module structures, complex environments, and high physical simulation fidelity. While most existing self-reconfigurable simulators view modules as actuated physical bodies with programmable controllers, RM3D views them as embodied agents, defined not only by their physical bodies (links, joints, docks, sensors, actuators) but also by their minds (actions, percepts, behaviors, world models) and the noise inherent in the interaction between sensors, actuators, and the environment. RM3D also simulates inter-module dock connection breakage, something novel for self-reconfigurable robot simulators. Additionally, we present experimental evidence showing that this novel architecture makes RM3D well-suited to locomotion, manipulation, reconfiguration, and embodied intelligence research.

Attachments: Video Attachment
Keywords: Cellular and Modular Robots, Distributed Robot Systems, Mechanism Design
Abstract: In this paper, we describe a novel self-assembling, self-reconfiguring cubic robot that uses pivoting motions to change its intended geometry. Each individual module can pivot to move linearly on a substrate of stationary modules. The modules can use the same operation to perform convex and concave transitions to change planes. Each module can also move independently to traverse planar unstructured environments. The modules achieve these movements by quickly transferring angular momentum accumulated in a self-contained flywheel to the body of the robot. The system provides a simplified realization of the modular actions required by the sliding cube model using pivoting. We describe the principles, the unit-module hardware, and extensive experiments with a system of eight modules.

Keywords: Cellular and Modular Robots
Abstract: A modular robot consists of a set of mechatronic modules that can be connected in many different ways, which makes it possible to build robots of many different shapes from the same basic set of modules. The main contribution of this work is an algorithm that, given the parameters of a module and the number of modules, efficiently can calculate how many different configurations and shapes can be built. These numbers are important because the first is a measure of the self-reconfigurability and the second, given there is a relationship between form and function, the versatility of a modular robot. As an experimental contribution, we enumerate the configuration and shape spaces of square, two-dimensional modules with all possible connector configurations. We proceed to three dimensions and enumerate the spaces of the theoretically interesting sliding cube module, and the M-TRAN and SuperBot modules. Several observations are made, an important one is that the shape spaces of the two physical modules are large even for a small number of modules (103 different shapes using 3 modules). This implies that it is not the lack of shape diversity that holds these modular robots back from being versatile. A result that suggests that if modules are designed right, versatility can potentially be reached even with few modules, which is contrary to the common belief in the community that more is better.

Attachments: Video Attachment
Keywords: Cellular and Modular Robots
Abstract: We describe a distributed and autonomous technique for dynamic gait adaptation for a chain-type, modular self-reconfigurable robot (MSR) using a fuzzy logic based, closed-loop controller. To maneuver itself, each module of the MSR is provided with a set of basic or fundamental gaits within a gait control table(GCT). A relevant problem in locomotion of a chain-type MSR is how to coordinate the gait of the individual modules with each other so that the desired locomotion of the MSR can be achieved. To address this problem, our proposed controller maps the inputs from the sensors of each module to an appropriate gait for the module determined from the goal and position of the module in the configuration, using a fuzzy technique. An inertial measurement unit (IMU) is used to close the loop between the goal and the module. We have verified the operation of our controller on a simulated 3-D model of an MSR called ModRED within the Webots robot simulator and also implemented it on the physical ModRED MSR. Our results illustrate that our controller can successfully adapt ModRED's locomotion by dynamically combining basic gaits from the individual modules in the configuration, regardless of the number of modules in the configuration and in the presence of noisy sensor inputs.

Attachments: Video Attachment
Keywords: Cellular and Modular Robots
Abstract: This paper presents the results of a study on the exploitation of compliance in structures made of self-reconfigurable modular robots - Roombots. This research was driven by the following three hypotheses: (1) compliance can improve locomotion performance; (2) different types of compliance will result in diverse locomotion behaviors; (3) control parameters optimized for a medium level of compliance will perform better for other values of compliance than parameters optimized for extremal compliance. Two types of in-series compliant elements were tested, with five different stiffness values for each of them, on a structure made of two Roombots modules. We ran dedicated on-line locomotion parameter optimizations for six different configurations and evaluated their performance for different stiffness values. Hypothesis 1 was confirmed for both types of compliant elements, with a peak of performance for an optimal level of compliance. The variety of locomotion strategies obtained for the different structures confirms hypothesis 2. Hypothesis 3 was only partially confirmed.

Keywords: Multi-Robot Coordination, Behaviour-Based Systems, Self-Organised Robot Systems
Abstract: Robotic clustering involves gathering spatially distributed objects into a single pile. It is a canonical task for selforganized multi-robot systems: several authors have proposed and demonstrated algorithms for performing the task. In this paper, we consider a setting in which heterogeneous strategies outperform homogeneous ones and changing the division of labor can improve performance. By modeling the clustering dynamics with a Markov chain model, we are able to predict performance of the task by different divisions of labor. We propose and demonstrate a method that is able to select an open-loop sequence of changes to the division of labor, based on this stochastic model, that increases performance. We validate our proposed method on physical robot experiments.

Keywords: Formal Methods in Robotics and Automation, Motion and Path Planning
Abstract: We propose a human-supervised control synthesis method for a stochastic Dubins vehicle such that the probability of satisfying a specification given as formula in a fragment of Probabilistic Computational Tree Logic (PCTL) over a set of environmental properties is maximized. Under some mild assumptions, we construct a finite approximation for the motion of the vehicle in the form of a tree-structured Markov Decision Process (MDP). We introduce an efficient algorithm, which exploits the tree structure of the MDP, for synthesizing a control policy that maximizes the probability of satisfaction. For the proposed PCTL fragment, we define the specification update rules that guarantee the increase (or decrease) of the satisfaction probability. We introduce an incremental algorithm for synthesizing an updated MDP control policy that reuses the initial solution. The initial specification can be updated, using the rules, until the supervisor is satisfied with both the updated specification and the corresponding satisfaction probability. We propose an offline and an online application of this method.

Keywords: Path Planning for Multiple Mobile Robots or Agents, AI Reasoning Methods, Planning, Scheduling and Coordination
Abstract: This paper addresses a problem of cooperative path finding (CPF) where the task is to find paths for agents of a group of agents. Each agent is given a starting and a goal position and its task is to reach the goal from the given start. When following the paths, agents must not collide with each other and must avoid obstacles. It is suggested to augment propositional encodings of CPF with a so called mutex reasoning. Mutex reasoning is trying to rule out unreachable situations to reduce the size of the search space. It is checked whether a given pair of locations is reachable by a given pair of agents cooperatively. If not occurrence of the pair of agents in the pair of vertices is forbidden. The performed experimental evaluation showed that mutex reasoning improves existent encodings by 2 to 5 times in terms of solving runtime when makespan optimal solutions are searched.

Keywords: Formal Methods in Robotics and Automation, Motion and Path Planning, Motion and Trajectory Generation
Abstract: We develop a method for the control of discrete-time nonlinear systems subject to temporal logic specifications. Our approach uses a coarse abstraction of the system and an automaton representing the temporal logic specification to guide the search for a feasible trajectory. This decomposes the search for a feasible trajectory into a series of constrained reachability problems. Thus, one can create controllers for any system for which techniques exist to compute (approximate) solutions to constrained reachability problems. Representative techniques include sampling-based methods for motion planning, reachable set computations for linear systems, and graph search for finite discrete systems. Our approach avoids the expensive computation of a discrete abstraction, and its implementation is amenable to parallel computing. We demonstrate our approach with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.

Keywords: Evolutionary Robotics, Navigation, Control Architectures and Programming
Abstract: Customising navigational control for autonomous robotic mapping platforms is still a challenging task. Control software must simultaneously maximise the area explored whilst maintaining safety and working within the constraints of the platform. Scoring functions to assess navigational options are typically written by hand and manually refined. As navigational tasks become more complex this manual approach is unlikely to yield the best results. In this paper we explore the automatic derivation of a scoring function for a ground based exploration platform. We show that it is possible to derive the entire structure of a scoring function and that allowing structure to evolve yields significant performance advantages over the evolution of embedded constants alone.

Attachments: Video Attachment
Keywords: Localization, Range Sensing
Abstract: We present a robust plane finding algorithm that when combined with plane-based frame-to-frame registration gives accurate real-time pose estimation. Our plane extraction is capable of handling large and sparse datasets such as those generated from spinning multi-laser sensors such as the Velodyne HDL-32E LiDAR. We test our algorithm on frame-to-frame registration in a closed-loop indoor path comprising 827 successive 3D laser scans (over 57 million points), using no additional information (e.g., odometry, IMU). Our algorithm outperforms, in both accuracy and time, three state-of-the-art methods, based on iterative closest point (ICP), plane-based randomized Hough transform, and planar region growing.

Keywords: Range Sensing, Localization, Mapping
Abstract: For purposes of real-time 3D sensing, it is important to be able to quickly register together incoming point cloud data. In this paper, we devise a method to quickly and robustly decompose large point clouds into a relatively small number of meaningful surface patches from which we register new data points. The surface patch representation sidesteps the costly problem of matching points to points since incoming data only need to be compared with the patches. The chosen parametrization of the patches (as Gaussians) leads to a smooth data likelihood function with a well-defined gradient. This representation thus forms the basis for a robust and efficient registration algorithm using a parallelized gradient descent implemented on a GPU using CUDA. We use a modified Gaussian Mixture Model (GMM) formulation solved by Expectation Maximization (EM) to segment the point cloud and an annealing gradient descent method to find the 6-DOF rigid transformation between the incoming point cloud and the segmented set of surface patches. We test our algorithm, Robust EM Segmentation (REM-Seg), against other GPU-accelerated registration algorithms on simulated and real data and show that our method scales well to large numbers of points, has a wide range of convergence, and is suitably accurate for 3D registration.

Keywords: Intelligent Transportation Systems, Collision Detection and Avoidance, Motion and Trajectory Generation
Abstract: Predicting other traffic participants trajectories is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It is also necessary for many Advanced Driver Assistance Systems, where the ego-vehicle's trajectory has to be predicted too. Even if trajectory prediction is not a deterministic task, it is possible to point out the most likely trajectory. This paper presents a new trajectory prediction method which combines a trajectory prediction based on Constant Yaw Rate and Acceleration motion model and a trajectory prediction based on maneuver recognition. It takes benefit on the accuracy of both predictions respectively a short-term and long-term. The defined Maneuver Recognition Module selects the current maneuver from a predefined set by comparing the center lines of the road's lanes to a local curvilinear model of the path of the vehicle. The overall approach was tested on prerecorded human real driving data and results show that the Maneuver Recognition Module has a high success rate and that the final trajectory prediction has a better accuracy.

Keywords: Intelligent Transportation Systems, Collision Detection and Avoidance
Abstract: For collision avoidance systems to be accepted by human drivers, it is important to keep the rate of unnecessary interventions very low. This is challenging since the decision to intervene or not is based on incomplete and uncertain information. The contribution of this paper is a decision making strategy for collision avoidance systems which allows the system to occasionally postpone a decision in order to collect more information. The problem is formulated in the framework of statistical decision theory, and the core of the algorithm is to run a preposterior analysis to estimate the benefit of deciding with the additional information. A final decision is made by comparing this benefit with the cost of delaying the intervention. The proposed approach is evaluated in simulation at a two-way stop road intersection for stop sign violation scenarios. The results show that the ability to postpone decisions leads to a significant reduction of false alarms and does not impair the ability of the collision avoidance system to prevent accidents.

Keywords: Intelligent Transportation Systems, Sensor Fusion
Abstract: In this paper, we propose and develop a framework for automatic switching of manual driving and autonomous driving based on driver drowsiness detection. We first present the scale-down intelligent transportation system (ITS) testbed. This testbed has four main parts: an arena; an indoor localization system; automated radio controlled (RC) cars; and roadside monitoring facilities. Second, we present the drowsiness detection algorithm which integrates facial expression and racing wheel motion to recognize driver drowsiness. Third, a manual and autonomous driving switching mechanism is developed, which is triggered by the detection of drowsiness. Finally, experiments were performed on the ITS testbed to demonstrate the effectiveness of the proposed framework.

Keywords: Intelligent Transportation Systems, Motion and Trajectory Generation, Navigation
Abstract: In this paper energy optimal solutions for the approach of red traffic lights are derived. As cars waste most of the fuel in city traffic and especially in queuing at traffic lights, the presented framework provides solutions to save fuel and to protect the environment. The solutions are obtained using the definition of spent physical work which has to be minimized. It covers both cases, that the time of switching of the traffic lights is known and that the time of switching can only be modeled as a stochastic process. For a known time of switching a continuous solution is derived using Pontryagin Minimum Principle; in the stochastic case a modified Bellmann equation is formulated. The latter is solved with dynamic programming techniques. The presented solutions can be used for autonomous driving as well as for driving assistant systems. Simulation results show the potential savings using the presented approach.

Keywords: Intelligent Transportation Systems, Visual Tracking, Computer Vision
Abstract: To be deployed in the real-world, automatic and semi-automatic systems should understand traffic rules by recognizing and comprehending contents of traffic signs, because traffic signs inform what driving behaviors should be. In this paper, we present the successful application of methods to improve the traffic sign localization performance. Given a potential sign region, our algorithm represents both the detected sign as a target and candidates in the subsequent frame as probability density functions. Then, our algorithm maximizes the similarity between a target and candidates to localize the sign. Finally, the maximum similarity among candidates is assigned as a tracked sign. The experimental results verify that our algorithm can robustly localize traffic signs in images under various weather conditions and driving scenarios.

Keywords: Intelligent Transportation Systems, Recognition, Computer Vision
Abstract: The presence of roadworks greatly affects the validity of prior maps used for navigation by autonomous vehicles. This paper addresses the problem of quickly and robustly assessing the gist of traffic scenes for whether road- works might be present. Without explicitly modelling individual roadwork indicators such as traffic cones, construction barriers or traffic signs, our method instead only exploits the engineered visual saliency of such objects. We draw inspiration from opponent colour vision in humans to formulate a novel roadwork scene signature based on an opponent spatial prior combined with gradient information. Finally, we apply our roadwork scene signature to the task of roadwork scene recognition, within a classification framework based on soft assignment vectorization and RUSBoost. We evaluate our roadwork signature on real life data from our autonomous vehicle.

Keywords: Motion Control
Abstract: In this paper, a Nonlinear Model Predictive Control (NMPC) is proposed to control a single stage Voice-Coil- Motor (VCM) of a Hard-Disk-Drive (HDD). Due to its fast settling time and its robustness, this controller is suggested to be applied for the first time to control a R/W head of an HDD. To highlight the good performance and characteristics of the NMPC, a comparative study with a standard PID control is presented. The two control methodologies were evaluated in nominal conditions as well as in other situations such as disturbances and uncertainties on the plant model parameters. In all cases, NMPC presents much better simulation results in term of speed and robustness in the presence of unexpected perturbations and parameters’ change.

Keywords: Motion Control, Aerial Robotics
Abstract: We present a novel method to control an X4-Flyer using kinodynamic motion planning. Kinodynamic motion planning is the planning technique of generating a control input by solving the problems of kinematic constraints and dynamic constraints simultaneously, and it is useful for simpler generation of the control input. In this paper, we extend existing kinodynamic motion planning, which uses “Harmonic potential field (HPF)” and some damping forces for the control of simple point mass, to the motion planning for an X4-Flyer, which is a complex multivariable system. Then, we use “nonlinear anisotropic damping forces (NADFs)”, which is proposed by Masoud, as damping force. In the simulation, a method using NADFs is compared with that using viscous damping forces. From the simulation, it is confirmed that the kinodynamic motion planning can be realized for an X4-Flyer.

Attachments: Video Attachment
Keywords: Motion Control, Nonholonomic Motion Planning
Abstract: An intelligent PID controller (i-PID controller) is applied to control the nonholonomic mobile robot with measurement disturbance. Because of the particularity of the nonholonomic systems, this paper propose to use a switching parameter alpha in the i-PID controller. We show in simulations that the proposed method is able to control the nonholonomic mobile robots with measurement disturbance, and it can also stabilize the robot at a static point.

Keywords: Motion Control, Sensor Fusion, Hydraulic/Pneumatic Actuators
Abstract: This paper presents closed-loop state feedback motion control of a heavy-duty hydraulic manipulator using solely micro-electro-mechanical systems (MEMS) rate gyroscopes and linear accelerometers for joint angular position, velocity and acceleration feedback. For benchmarking, incremental encoders with 2 million counts per revolution are also used to supply the joint motion state feedback. The two motion state estimation methods are compared using Cartesian path trajectory closed-loop control experiments with both position feedback-based proportional control and motion state-based feedback control. The experiments show that the proposed MEMS-based state feedback control yields comparable tracking results compared with the high accuracy encoder. Furthermore, the MEMS-based angular acceleration estimation in particular is free from typical differentiation induced noise amplification and post-filtering phase-lag.

Attachments: Video Attachment
Keywords: Motion Control, Hydraulic/Pneumatic Actuators, Force Control
Abstract: Hydraulic actuators are well-known for their high power-to-weight ratio, rapid responses, compactness and reliable performance. However, one of the drawbacks of fluid power systems have been large energy losses. In this paper, our research objective is to develop both energy-efficient and high performance motion controller for heavy-duty hydraulic manipulators. We apply an unconventional servo meter-in meter-out hydraulic valve control set-up that is used to decouple hydraulic actuator load pressure level from load force to improve energy efficiency. The developed control system is based on the Virtual Decomposition Control (VDC) approach to guarantee the closed-loop system stability of the multi degree of freedom heavy-duty hydraulic crane driven by an unconventional Servo Meter-In Meter-Out (SMIMO) control set-up. Capability for approximately 42% lower energy consumption was achieved in the Cartesian motion trajectory experiments with the proposed novel controller compared with a conventional 4-way servo valve set-up, without significant control performance deterioration.

Keywords: Motion Control, Manufacturing and production systems, Industrial Robots
Abstract: In this paper, a novel contouring control method based on natural local approximation of desired contour in task frame is proposed for multi-axis control systems. Based on local geometry properties, natural local approximation can achieve more accurate contouring error estimation compared with other local approximation methods for both planar and spatial contouring tasks. The contouring controller, integrated with a PD controller cooperated with the feedback linearization technique and a feedforward compensation, is designed to realize the decoupling control of estimated errors in the task frame. Contouring performance can then be improved directly by increasing corresponding controller parameters. Simulations of 3-axis system and experiments on biaxial XY-stage verified that our proposed method can reduce the contouring errors dramatically in high speed and large curvature cases compared with first-order based method.

Attachments: Video Attachment
Keywords: Hydraulic/Pneumatic Actuators, Mechanism Design, Medical Robots and Systems
Abstract: Many kinds of power assist device have been developed, and are driven with various actuators such as an electric motor, a hydraulic cylinder and so on. By using the exoskeleton, a high generated torque actuator can be introduced. An assist performance of these devices becomes high. On the other hand, a realization of exoskeleton which has the same D.O.F of a human is not easy from considerations about a size and strength of device. In this study, the power assist wear for lower limb is developed. The developed wear is like trousers. A human can be assisted by just wearing trousers on which the pneumatic soft actuators are put. The pneumatic soft actuator has a high power weight ratio, and has a light weight. These features contribute to realize the simple structure which is like clothes. In this paper, the structure of power assist wear is discussed, and the application of power assist wear to assist going up and down stairs are described.

Keywords: New Actuators for Robotics, Hydraulic/Pneumatic Actuators, Rehabilitation Robotics
Abstract: Conventional pneumatic actuators have been a popular choice due to their decent force/torque output. Nowadays, new generation of pneumatic actuator made out of highly compliant elastomers, which we call soft pneumatic actuators (SPA), are drawing increasing attention due to their ease of fabrication, high customizability and innately softness. However, there is no effective method presented to characterize and understand these actuators, such as to measure the force and torque output, range of motion and the speed of actuation. In this work, we present two types of SPAs: bending and rotary actuators. In addition, we have developed two measurement setups to characterize actuators of different geometries. The measured force/torque outputs of different actuators are presented and analyzed. Step responses to certain pressure input are presented and discussed. A simple model is presented to provide physical insight to the observed behavior of the soft actuators. This work provides the basis for designing customized SPAs with application-specific requirements.

Attachments: Video Attachment
Keywords: Hydraulic/Pneumatic Actuators, Biologically-Inspired Robots, Biomimetics
Abstract: This study aims at development of a multi-directional bending mechanism with long length driven by fluidic rubber actuators. Generally bending mechanisms with fluidic rubber actuators can have advantages of smooth and continuous motion, however because of low stiffness; it is difficult to generate high output force. To solve the problem, we have proposed a novel bending mechanism combined with contracting and extending rubber actuators. By bundling rubber actuators with different motion types, the developed bending mechanism can have the high stiffness. In this report, optimized extending and contracting rubber actuators are made basis on a McKibben actuator, then they are combined to be the bending mechanism. Experimentally stiffness of the mechanism is measured and is compared with a bending mechanism bundled with same motion type actuators. Resulting high stiffness can be recognized by the proposed mechanism. Additionally, a very long bending mechanism, which is 7m in length, is developed and its motion is demonstrated.

Keywords: Hydraulic/Pneumatic Actuators, New Actuators for Robotics, Biologically-Inspired Robots
Abstract: Soft actuators are found throughout nature from elephant trunks to round worms, demonstrating large specific forces without the need for sliding components. These actuators offer impact resilience, human-safe interaction, versatility of motion, and scalability in size. Biological structures often use a fiber-reinforcement around a fluid filled elastomeric enclosure, in which the elastomeric material will capture the distributed pressure and transfer it to the fibers, which will in turn direct the forces to the ends. We previously discovered an entire domain of fiber-reinforced elastomeric enclosures (FREEs), of which McKibben actuators are a small subset. The range of forces and moments possible with FREEs has not been previously investigated. 45 FREE actuators across the span of fiber angle configurations were fabricated and tested. The reaction force and moment of each actuator was determined across a gamut of pressures. Analytical models were generated using a variety of simplifying assumptions. These models were created to provide a closed form expression that models the force and moment data. The models were compared to the experimental values to determine their fit; this provides an understanding of which simplifying kinematic assumptions best represent the experimental results. Interpolated experimental results and the analytical models are all graphically represented for use as an intuitive design tool.

Keywords: Hydraulic/Pneumatic Actuators, Biomimetics, Compliance and Impedance Control
Abstract: In this paper, a joint control algorism was proposed to implement on our musculoskeletal robot. The joints are all actuated by pneumatic muscles and have antagonistic structure. In order to gain a better performance, we first modeled the pneumatic muscle, and then considering the dynamics two control method was discussed and compared. As a tradeoff of rapidity and accuracy, the combined joint control algorism was implemented on the robot system. The algorism could tune the stiffness of the joint automatically to fit the compliance need for joint control. The experiments on our robot showed that the joint control algorism could operate the robot with a fast and accurate response. There is nearly not lagging behind, and with a small overshot during the step testing, and a complex leg’s trajectory was also achieved through our joint controller.

Keywords: Hydraulic/Pneumatic Actuators, Force and Tactile Sensing, Force Control
Abstract: The importance of force measurement and backdrivability in realizing force sensitive actuator is widely acknowledged. There are studies on fidelity of torque sensors and backdrivability individually, but limited study are made on investigating effect of torque fidelity and backdrivability on force sensitivity of the actuation system. In this paper, we developed backdrivable electro-hydrostatic actuator equipped with torque sensor to analyze the effect of torque fidelity and backdrivability on force sensitive control system. We implemented friction compensation controller and evaluated force sensitivity of the actuator by residual friction torque after the friction compensation. Method using pressure sensor and torque sensor were compared. Effect of backdrivability was performed by comparing friction torque of Harmonic Drive joint and joint with developed actuator.

Keywords: Haptics and Haptic Interfaces
Abstract: This study proposes a novel technique to display tactile sensation using electro-rheological fluid (ERF). ERF changes its rheological characteristics according to the electric field applied. The ERF used in this study generates relatively high yield stress and behaves as a solid when subjected to a strong electric field. Using this solid-liquid phase transition, we propose a novel device which provides a tactile sensation, i.e., tactile bump display. Applying electric field at a specific position in an ERF chamber, the corresponding ERF behaves as solid at the position. This solid-state ERF gives tactile sensation like a physical bump to a user. We fabricate in this study a prototype, which may realize the above-mentioned idea, and characterize it. We obtained the following results by experiments. First, the tactile bump display could make the users recognize their finger position on a flat surface by creating a tactile bump. Second, we confirmed that the tactile bump might dramatically improve the accuracy and the precision of touch typing.

Keywords: Haptics and Haptic Interfaces
Abstract: Abstract—In this paper a fabric yielding softness display (FYD-2) is proposed, where the stretching state is controlled using two motors, while the contact area is measured in real-time. In previous works, authors proposed a fabric-based device, with embedded contact area measurement system, which was proved to provide subjects with a compelling and naturalistic softness perception. Compared to it, FYD-2 exhibits reduced dimensions, a more accurate sensorization scheme and an increased actuation velocity, which allows to implement fast changes in the stiffness levels. Furthermore, FYD-2 is endowed with an additional degree of freedom that can be used to vehiculate additional haptic cues. In this work we describe the mechanical design and the mathematical model of the device. The reliability in real-time tracking of force-area curves of real objects is demonstrated.

Keywords: Contact Modelling, Force and Tactile Sensing, Dexterous Manipulation
Abstract: We have proposed a Beam Bundle Model for modeling of a human fingertip during pushing and sliding action with friction, especially stick-to-slip transition, to overcome mentioned issues. In order to construct its three-dimensional non-homogeneous structure, we took sequence of magnetic resonant images, which bring consecutive cross-sectional layers of the human fingertip with distribution of skin, tissue, bone, and nail. Simulation results show a twofold aspect. Firstly, it can generate not only normal force distribution caused by pushing, but also response of friction force during sliding. Secondly, and more interestingly, the model dynamically produces localized displacement phenomenon on the contact area during stick-to-slip phase, which indicates how slippage propagate in the contact area before the total slippage of the fingertip occurs. Finally, we investigated role of sliding mechanism acting on human fingertips' contact area in stable lifting of an object, in order to show the potential of the model in studying tactile mechanism of human and apply to robotic systems.

Keywords: Haptics and Haptic Interfaces
Abstract: It is a challenging problem to achieve fast and realistic six degree-of-freedom (DOF) haptic simulation of scenarios involving large number of multi-region contacts. In this paper, we propose an optimization-based constrained method enhanced by parallel quadratic programming to solve the rendering problem. Hierarchical sphere-tree models are used to represent the moving haptic tool and its surrounding static objects. Given a moving graphic tool as the avatar of the haptic tool in the virtual environment, we compute its quasi-static motion by solving a configuration-based optimization. Instead of using traditional active-set method, we transform the original optimization problem into its dual problem and solve the optimum about the graphic tool using a parallel quadratic programming method. Our algorithm has been implemented with a 6-DoF Phantom Premium 3.0. We validate the proposed algorithm in several benchmarks involving complex, large-region contacts. The results demonstrate that the proposed method can achieve a two to three times speed improvement than the active-set method. A further speed-up for haptic rendering may be achieved by the parallel implementation on parallel processor such as graphic processing units.

Keywords: Haptics and Haptic Interfaces
Abstract: Controlling haptic devices in an optimal way is crucial to achieve both, best performance and most realistic haptic feedback. The present article investigates control design of a single degree of freedom haptic device that is interacting with a human operator and rendering a virtual wall affected by time delay. To this end, it suggests different optimization criteria based on the step response of the haptic system. These criteria cover fundamental requirements for efficiently using haptic devices, particularly fast settling and minimum overshoot. For each criterion an optimal path and point inside the stable region of the virtual wall parameters is derived. These optima depend mainly on the system mass, sampling time and time delay. This approach is supported by experiments on two devices, a Falcon haptic device and a DLR/KUKA Light-Weight Robot arm.

Keywords: Haptics and Haptic Interfaces, Contact Modelling
Abstract: Enhancing the realism of the perceived contact force is a primary challenge in haptic rendering of virtual walls (VWs) and objects (VOs). For VOs, this goal directly translates into accurate rendering of not only stiffness, but also mass. The most challenging situation arises when the stiffness of the object is large, its mass is small, and sampling is slow. To address this challenge, a framework entitled high-fidelity haptic rendering (HFCR) has been developed. The HFCR framework is composed of the following three main strategies: an energy-consistent rendering of the contact force, smooth transition between contact modes, and remaining leak dissipation. The essence of all these strategies is to make the energy of the VO emulate its continuous-time counterpart. This is achieved through physically meaningful modifications in the constitutive relations to suppress artificial energy leaks. This paper reports simulation and experiments involving the one-dimensional canonical model of a VO to illustrate the HFCR framework and compare it to the existing methods. Results demonstrate the promising stability and force rendering fidelity of this framework.

Attachments: Video Attachment
Keywords: Manipulation Planning and Control, Parts Feeding and Fixturing, Contact Modelling
Abstract: This paper presents a throwing motion planner based on a goal manifold for two-point boundary value problem. The article outlines algorithmic and geometric issues for planar throwing of rigid objects with a nonprehensile end-effector. Special attention is paid to the challenge of controlling a desired 6-dimensional state of the object with a planar 3- DoF robot. Modeling of the contacts is discussed using a state vector of the coupled robot and object dynamics. Robustness against uncertainty due to varying model parameters such as object inertia and friction between the end-effector and the object is investigated. An approach for obtaining manifolds of terminal constraints from the goal configuration is described. Classification of these constraints is given. Finally, feasible trajectory generation conditions for successful execution of the generated optimal controls are discussed.

Attachments: Video Attachment
Keywords: Manipulation Planning and Control
Abstract: We present a method to manipulate deformable objects that does not require modeling and simulating deformation. Our method is based on the concept of diminishing rigidity, which we use to quickly compute an approximation to the Jacobian of the deformable object. This Jacobian is used to drive the points within the deformable object towards a set of targets. However, this Jacobian alone is insufficient to avoid stretching the object beyond its allowed length and to avoid gripper collision with obstacles. Thus a key part of our approach is incorporating techniques to avoid collision and excessive stretching. Our experiments show how to perform several interesting tasks for one and two-dimensional deformable objects using our method. They also show how the method can be applied to collaborative tasks, where the robot and a user simultaneously manipulate the deformable object. Our experiments are conducted in simulation but we emphasize that our method does not have access to the model of the deformable object used by the simulator, although we assume we are able to sense the geometry of the object. While our method is local, we find that it is quite versatile in the range of tasks it can perform, especially since it has no knowledge of the model of the deformable object.

Keywords: Multifingered Hands, Grasping, Dexterous Manipulation
Abstract: In order to realize performance gain of a robot or an artificial arm, the end-effector which exhibits the same function as human beings and can respond to various objects and environment needs to be realized. Then, we developed the new hand which paid its attention to the structure of human being's hand　 which realize operation in human-like manipulation　 (called TUAT/Karlsruhe Humanoid Hand). Since this humanoid hand has the structure of adjusting grasp shape and grasp force automatically, it does not need a touch sensor and feedback control. It is designed for the humanoid robot which has to work autonomously or interactively in cooperation with humans and for an artificial arm for handicapped persons. The ideal end-effectors for such an artificial arm or a humanoid would be able to use the tools and objects that a person uses when working in the same environment. If this humanoid hand can operate the same tools, a machine and furniture, it may be possible to work under the same environment as human beings. As a result of adopting a new function of a palm and the thumb, the robot hand could do the operation which was impossible until now. The humanoid hand realized operations which hold a kitchen knife, grasping a fan, a stick, uses the scissors and uses chopsticks.

Attachments: Video Attachment
Keywords: Manipulation Planning and Control, Grasping, Localization
Abstract: We investigate the problem of estimating the state of an object during manipulation. Contact sensors provide valuable information about the object state during actions which involve persistent contact, e.g. pushing. However, contact sensing is very discriminative by nature, and therefore the set of object states that contact a sensor constitutes a lower-dimensional manifold in the state space of the object. This causes stochastic state estimation methods, such as particle filters, to perform poorly when contact sensors are used. We propose a new algorithm, the manifold particle filter, which uses dual particles directly sampled from the contact manifold to avoid this problem. The algorithm adapts to the probability of contact by dynamically changing the number of dual particles sampled from the manifold. We compare our algorithm to the conventional particle filter through extensive experiments and we show that our algorithm is both faster and better at estimating the state. Unlike the conventional particle filter, our algorithm's performance improves with increasing sensor accuracy and the filter's update rate. We implement the algorithm on a real robot using commercially available tactile sensors to track the pose of a pushed object.

Attachments: Video Attachment
Keywords: Manipulation Planning and Control, Grasping, Motion and Path Planning
Abstract: This paper presents a novel methodology for planning the movements of a robotic hand when a precision grasp is going to be performed. The approach used is based on the standard Fast Marching Square (FM2) path planning method and its application to robot formations motion planning. In this case, the hand is considered to be a kinematic chain in which a mobile robot is located at every joint position. The robot formation is therefore deformable among the positions allowed by the mechanical limits of the joints. To perform a given precision grasp, the task is divided into two phases. First the hand approaches the object. FM2 is used to calculate a fast and smooth path towards the object to be grasped. While the hand is covering it, the formation updates its shape according to the map of velocities calculated in FM2. The second phase consists on performing the precision grasp. Every finger is modelled as a robot formation and a path is calculated for each fingertip so that they reach the grasping points on the object. The position of the joints of the fingers is computed using an inverse kinematics algorithm. Simulations show the usefulness of this approach thanks to a good performance of the approaching and the grasping tasks.

Attachments: Video Attachment
Keywords: Manipulation Planning and Control, Learning from Demonstration, Integrated Task and Motion Planning
Abstract: The goal of this study is to provide an architecture for a generic definition of robot manipulation actions. We emphasize that the representation of actions presented here is "procedural". Thus, we will define the structural elements of our action representations as execution protocols. To achieve this, manipulations are defined using three levels. The top-level defines objects, their relations and the actions in an abstract and symbolic way. A mid-level sequencer, with which the action primitives are chained, is used to structure the actual action execution, which is performed via the bottom level. This (lowest) level collects data from sensors and communicates with the control system of the robot. This method enables robot manipulators to execute the same action in different situations i.e. on different objects with different positions and orientations. In addition, two methods of detecting action failure are provided which are necessary to handle faults in system. To demonstrate the effectiveness of the proposed framework, several different actions are performed on our robotic setup and results are shown. This way we are creating a library of human-like robot actions, which can be used by higher-level task planners to execute more complex tasks.

Attachments: Video Attachment
Keywords: Flexible Arms, Grasping, Biologically-Inspired Robots
Abstract: Continuum manipulators, inspired by invertebrate structures in nature, such as octopus arms and elephant trunks, do not contain rigid links, can deform, and are passively compliant, which make them particularly flexible for manipulation in cluttered space. A key open issue here is how to make such a manipulator autonomously grasp an object in cluttered space, especially if the object cannot be completely seen or known before being grasped. In this paper, we address this issue by introducing an approach that enables a multi-section continuum manipulator to probe an object with its tip while gradually form a whole-arm, force-closure grasp by following closely the contour of the probed object. This real-time approach is both effective and efficient for grasping an object in a cluttered space, as evident from the test examples.

Attachments: Video Attachment
Keywords: Flexible Arms, Grasping, Biologically-Inspired Robots
Abstract: A continuum manipulator, such as a multi-section trunk/tentacle robot, is promising for deft manipulation of a wide range of objects of different shapes and sizes. Given an object, a continuum manipulator tries to grasp it by wrapping tightly around it. Autonomous grasping requires real-time determination of whether an object can be grasped after it is identified, and if so, the feasible whole-arm wrapping around configurations of the robot to grasp it, which we call grasping configurations, as well as the path leading to a grasping configuration. In this paper, we describe the process for autonomous grasping from object detection to executing the grasping motion and achieving force-closure grasps, with a focus on a general analysis of all possible types of planar grasping configurations of a three section continuum manipulator. We further provide conditions for existence of solutions and describe how to find a valid grasping configuration and the associated path automatically if one exists. Experimental results with the OctArm manipulator validate our approach, and shows that the entire process to determine an autonomous grasping operation, which includes automatic detection of the target object and determination of a grasping configuration and a path to the grasping configuration that avoids obstacles, can take just a small fraction of a second. Once a grasping configuration is reached, the manipulator can lift the object stably,i.e.,a force-closure grasp can be achieved.

Keywords: Flexible Arms, Biologically-Inspired Robots
Abstract: This paper presents the results of a multidisciplinary project where biologists, mechanical engineers and electronic engineers worked together to develop bio-inspired soft continuum arms, whose design captures and takes advantage of key features of the octopus anatomy and control. The cross-integration of such diverse expertise was channelled towards the design of soft continuum arms whose characteristics were inspired by nature, but with a focus on readily available engineering technologies and their effective integration from a system viewpoint. On one side the mechanical structure and the control was designed looking at the animal, in particular at the coupling between its anatomy and control system that allows the animal to survive in its ecosystem. On the other side engineering issues and constraints were carefully accounted for, namely material softness, intrinsic safety, energy efficiency, cost effectiveness and manufacturing aspects. The design evolution is presented through three different generations of prototypes where both bio-inspiration and engineering requirements are appropriately blended.

Keywords: Flexible Arms, Mechanism Design
Abstract: In this paper, we investigate the property of an impulse force generator based on snap-through buckling of a robotic closed elastic rod which is considered as one of good examples of continuum robots. The impulse force generator considered here utilizes a snap through buckling of an elastic rod where its base end is pinned and driven by a rotary actuator forcibly while the tip end is pinned or clamped to the fixed point. One of the most fundamental design problems is to maximize the released elastic energy at each buckling state subject to limited ranges of driving torque and angle of a given actuator. From this design viewpoint, we show two findings obtained from quasi-static planar shape transition simulation of the closed elastica, which will be useful for a design of the robot, that is, the ratio of the elastica length and the endpoint distance decides 1) the buckling angle which relates to the range of an actuator driving angle, and 2) the released elastic energy per the maximum driving torque. We also provide a mathematical description of snap-through buckling based on which we can measure a distance to a buckling point.

Attachments: Video Attachment
Keywords: Biologically-Inspired Robots, Biomimetics, Underactuated Robots
Abstract: Soft and continuum robots have the useful capability of adopting intricate postures and conforming to complex shapes. Furthermore, structures built from soft materials propagate mechanical energy from one part of the body to another, depending on its body shape, boundary condition, stiffness distribution, and so on. This makes the robots capable of producing a large number of force profiles to achieve useful behaviors and functionalities, even using a small number of actuators. Exploiting the soft mechanical property also enables to generate functional frictional forces, which is a key issue in controlling robot locomotion. In this paper, a highly deformable 3-D printed soft robot (PS robot) is presented, which is capable of generating complex, robust gaits on different inclines using a novel variable friction leg design. This design changes the frictional force depending on the robot posture and shape to facilitate robot locomotion. Shape memory alloy (SMA) coils are embedded into the robot in such a way that they act both as structural elements and actuators. This is the first soft robot platform produced by 3-D printing making fabrication simple and fast.

Keywords: Biologically-Inspired Robots, Biomimetics, Kinematics
Abstract: Bio-inspired micro-robots are of great importance as to implement versatile microsystems for a variety of in vivo and in vitro applications in medicine and biology. Accurate models are necessary to understand the swimming and rigidbody dynamics of such systems. In this study, a series of experiments are conducted with a two-link cm-scale bioinspired robot moving vertically without a tether, in siliconefilled narrow cylindrical glass channels. Swimming velocities are obtained for a set of varying tail and wave geometries, and employed to validate a resistive force theory (RFT) model using modified resistance coefficients based on measured forward velocity and body rotation rates.

Keywords: Physical Human-Robot Interaction, Cooperating Robots, Haptics and Haptic Interfaces
Abstract: This paper investigates human-robot cooperative swinging of a complex pendulum-like object. The complexity of the object results in two possible swinging modes. The goal is to excite one mode such that a desired energy level of the pendulum is reached while simultaneously damping the other mode. The energy based control concept relies on the projection of the complex mechanism onto an abstract simple pendulum with two-sided actuation. An actively contributing robot leader and robot follower are implemented. The controller performance is analyzed through simulations. A virtual reality experiment shows the transferability of the control approach to a human interaction partner.

Attachments: Video Attachment
Keywords: Physical Human-Robot Interaction, Human and humanoid skills/cognition/interaction
Abstract: In this paper, a first step is taken towards using vision in human-humanoid haptic joint actions. Haptic joint actions are characterized by physical interaction throughout the execution of a common goal. Because of this, most of the focus is on the use of force/torque-based control. However, force/torque information is not rich enough for some tasks. Here, a particular case is shown: height stabilization during table carrying. To achieve this, a visual servoing controller is used to generate a reference trajectory for the impedance controller. The control law design is fully described along with important considerations for the vision algorithm and a framework to make pose estimation robust during the table carrying task of the humanoid robot. We then demonstrate all this by an experiment where a human and the HRP-2 humanoid jointly transport a beam using combined force and vision data to adjust the interaction impedance while at the same time keeping the inclination of the beam horizontal.

Keywords: Physical Human-Robot Interaction, Human-Humanoid Interaction, Learning from Demonstration
Abstract: In this work we present a framework for kinesthetic teaching and iterative refinement of whole body motions. For detection of external forces we apply a momentum based disturbance observer known from manipulator control to the floating-base model of a humanoid robot. These external forces are used as a trigger for implementing a compliant behavior at the interaction point and are integrated into a predictive balancing algorithm. For representation of the motion data, a hidden Markov model is used, which allows for an iterative update of the discrete motion states as well as a smooth generation of continuous motion data. Finally, we present an application of these algorithms on the humanoid robot TORO.

Keywords: Cognitive Human-Robot Interaction, Cooperating Robots, Robot Safety
Abstract:

The development of trustworthy human-assistive robots is a challenge that goes beyond the traditional boundaries of engineering. Essential components of trustworthiness are safety, predictability and usefulness. In this paper we demonstrate that the integration of joint action understanding from human-human interaction into the human-robot context can significantly improve the success rate of robot-to-human object handover tasks. We take a two layer approach. The first layer handles the physical aspects of the handover. The robot's decision to release the object is informed by a Hidden Markov Model that estimates the state of the handover. Inspired by human-human handover observations, we then introduce a higher-level cognitive layer that models behaviour characteristic for a human user in a handover situation. In particular, we focus on the inclusion of eye gaze / head orientation into the robot's decision making. Our results demonstrate that by integrating these non-verbal cues the success rate of robot-to-human handovers can be significantly improved, resulting in a more robust and therefore safer system.

Attachments: Video Attachment
Keywords: Human-Robot Interaction, Redundant Robots, Robot Safety
Abstract: Tight human-robot interaction and collaboration will characterize future robot tasks. Robot working environments will be increasingly unstructured, as safety barriers will be removed to allow a continuous cooperation of robotic and human workers. Such a working scenario calls for novel safety systems capable of combining productivity with workers' safety. In this paper, a method for the definition of a task-consistent collision avoidance safety strategy is presented. A classification of task constraints based on relevance for task completion is introduced. Control of task constraints enforcement is performed through a state machine. A template for such state machine is proposed. Experimental validation of the proposed safety system on a dual-arm industrial robot prototype is presented.

Keywords: Robot Safety, Physical Human-Robot Interaction, Redundant Robots
Abstract: Human-robot collision has drawn increasing attention in recent years and collision safety can be improved by successfully detecting collisions between a human and a robot. For a manipulator working in human environments, collisions usually occur at the manipulator body while the robot performs a contact task using its end-effector to interact with the environment. Therefore, both collision force and the force on the end-effector contribute to the external torques which can be estimated from the robot dynamics and the joint torques measured by the joint torque sensors, which means whether or not a collision has occurred cannot be reliably determined using this estimation. In this study, we propose a novel collision detection index to detect collisions independently of the end-effector force of a redundant manipulator equipped with joint torque sensors. Using the null space projection of a redundant manipulator, the collision detection index can be expressed as a function of the torque generated by a collision and the manipulator configuration. The proposed index is verified through various simulations. Simulation results show that collisions can be reliably detected regardless of the presence of the end-effector forces even in situations with external torques contaminated by substantial error.

Keywords: Humanoid and Bipedal Locomotion, Rehabilitation Robotics, Mechanism Design
Abstract: The paper reports on a novel hybrid drive lower-extremity exoskeleton research platform, XoR2, an improved version of XoR. Its design concept, details of the new hardware and basic experimental results are presented. The robot is designed so that it does not interfere with the user's normal walking and supports a 30-kg payload in addition to its own weight of 20 kg. The robot has a total of 14 joints; among them six flexion/extension joints are powered. Pneumatic artificial muscles are combined with small high-response servo motors for the hip and knee joints, and arranged antagonistically at the hip and ankle joints to provide passive stability and variable stiffness. The preliminary experimental results on position and torque control demonstrate that the proposed mechanisms, sensors and control systems are effective, and hybrid drive is promising for torque-controllable, high-speed, backdrivable, mobile (but non-power-autonomous) exoskeleton robots.

Attachments: Video Attachment
Keywords: Humanoid Robots, Tendon/Wire Mechanism, Biomimetics
Abstract: Human knee joint has a yaw-axis rotational DOF and a locking mechanism called screw-home mechanism. We focus on this mechanism and implement it to a musculoskeletal humanoid through hardware design. The importance of developing a knee joint with screw-home mechanism is that such a joint is capable of working yaw-axis properly and generating enough pitch joint torque for supporting whole body motion. In this paper, as an evaluation of our developed knee joint, we first checked the moment arm of the yaw rotational axis of the knee. Moreover, we also checked the yaw angle displacement during squat motion. From these results, we confirmed that the mechanism worked properly. Second, in order to check whether enough pitch joint torque is generated during movement, we conducted several experiments with whole body motions such as squatting. Lastly, as unique and integrated motions that involve the use of yaw DOF derived from the mechanism, we tested knee joint Open-Close, Right-to-Left and whole body twist squat motion. Our results demonstrated the feasibility of musculoskeletal humanoids with screw-home mechanism and showed that we have achieved humanlike twisting motion.

Keywords: Humanoid and Bipedal Locomotion
Abstract: The paper reports on a hydraulic robotic leg, a research platform suitable for exploring high-performance legged locomotion. We propose to use hydraulic linear actuators combined with lightweight links made out from carbon-fiber-reinforced plastic so that we can maximally enjoy their innate high load-to-weight ratio. The robot is designed so as to have a one-to-one mass ratio between the actuators and other parts. Based on the hydraulic servo actuator dynamics, the paper describes the details of velocity and force control of the robot joints, along to our passivity-based force control framework. Details on the hardware including the mechanisms, microcontrollers, and simulators are also described. Finally, the paper provides experimental results on high-speed swing control, zero-force tracking control, gravity compensation, task-space impedance control, and jumping. The experimental results demonstrate that the proposed system is actually effective for humanoid research platforms to explore agile legged locomotion.

Attachments: Video Attachment
Keywords: Legged Robots, Joint/Mechanism, Cellular and Modular Robots
Abstract: Legged robots are able to move across irregular terrains and some can be energy efficient, but are often constrained by a limited range of gaits which can limit their locomotion capabilities considerably. This paper reports a reconfigurable design approach to robotic legged locomotion that produces a wide variety of gait cycles, opening new possibilities for innovative applications. In this paper, we present a distance-based formulation and its application to solve the position analysis problem of a standard Theo Jansen mechanism. By changing the configuration of a linkage, our objective in this study is to identify novel gait patterns of interest for a walking platform. The exemplary gait variations presented in this work demonstrate the feasibility of our approach, and considerably extend the capabilities of the original design to not only produce novel cum useful gait patterns but also to realize behaviors beyond locomotion.

Keywords: Legged Robots, Climbing robots, Biologically-Inspired Robots
Abstract: In this paper, a harvestman-like hexapod walking robot named ASURA I is proposed and its leg mechanism design is discussed. Modeled on a harvestman in nature, the authors have introduced the concept of mobile form that has long legs and small body to ASURA I to enhance mobile performance on rough terrain. To develope long legs relative to body, special parallel link mechanism to drive leg joints powerfully and effectively is introduced to leg mechanism of ASURA I. First, we discusse design problems of leg mechanism in detail: leg length, DOF configuration, actuator selection and leg driving system. Then, analysis of kinematics, singularity and static characteristics of leg mechanism are reported. Finally, the prototype leg, which is 1.3 m in length and 3.2 kg in weight, has been developed and tested on some basic performance. The prototype successfully have demonstrated very basic motion.

Keywords: Legged Robots, Wheeled Robots, Space Robotics and Automation
Abstract: Identification of the wheel sinkage of exploration rovers provides valuable insight into the characteristics of deformable soils and thus the ease of traversal is also identified. In this paper we propose a simple vision based approach that robustly detects and measures the sinkage of any shaped wheel in real-time and with little sensitivity to various operating conditions. The method is based on color-space segmentation to identify the wheel contour and consequently the depth of the sinkage. In addition, our approach also provides a dynamic sinkage analysis which potentially allows for the identification of non-geometric hazards. The robustness of the algorithm has been validated for poor lighting, blurring, and background noise. The experimental results presented are for a hybrid legged wheel from our in-house single-wheel test-bed.

Keywords: Mapping, Computer Vision
Abstract: Extensive literature has been written on occupancy grid mapping for different sensors. When stereo vision is applied to the occupancy grid framework it is common, however, to use sensor models that were originally conceived for other sensors such as sonar. Although sonar provides a distance to the nearest obstacle for several directions, stereo has confidence measures available for each distance along each direction. The common approach is to take the highest-confidence distance as the correct one, but such an approach disregards mismatch errors inherent to stereo.

In this work, stereo confidence measures of the whole sensed space are explicitly integrated into 3D grids using a new occupancy grid formulation. Confidence measures themselves are used to model uncertainty and their parameters are computed automatically in a maximum likelihood approach. The proposed methodology was evaluated in both simulation and a real-world outdoor dataset which is publicly available. Mapping performance of our approach was compared with a traditional approach and shown to achieve less errors in the reconstruction.

Keywords: Mapping, Range Sensing, Navigation
Abstract: A widely used technique for constructing two dimensional maps employing range sensors is occupancy grid mapping assuming normal distributed sensor errors. An alternative to the grid map model with its fixed grid cell size are variable resolution grid maps, e.g. quadtrees. In this paper, the authors propose an approach for building occupancy quadtree maps assuming unknown but bounded sensor errors. Therefore, they examine possible types of sensor uncertainty when using laser rangefinders. They show that the majority of possible types of sensor errors can be covered much better by bounded error models than by probabilistic models. Hence, a novel inverse sensor model has been developed that incorporates measurement and pose uncertainty in a mathematical straightforward way using interval analysis. With this model, an approach for incrementally building occupancy quadtree maps is proposed. A first real world experiment has shown the applicability of the approach. Moreover, the authors compare the map with its probabilistic grid map counterpart. The bounded error quadtree has proved to be conservative but more reliable than the conventional probabilistic grid map.

Attachments: Video Attachment
Keywords: Mapping, SLAM
Abstract: Autonomous vehicles operating in real-world industrial environments have to overcome numerous challenges, chief among which is the creation and maintenance of consistent 3D world models. This paper focuses on a particularly important challenge, i.e., mapping in dynamic environments. We introduce several improvements to the recently proposed Normal Distributions Transform Occupancy Map (NDT-OM) aimed for efficient mapping in dynamic environments. A careful consistency analysis is given based on convergence and similarity metrics specifically designed for evaluation of NDT maps in dynamic environments. We show that in context of mapping with known poses the proposed method results in improved consistency and in superior runtime performance, when compared against 3D occupancy grids at same size and resolution. Additionally, we demonstrate that NDT-OM features real-time performance in highly dynamic 3D mapping and tracking scenario with centimeter accuracy over 1.5km trajectory.

Keywords: Mapping, SLAM
Abstract: Autonomous vehicles operating in real-world industrial environments have to overcome numerous challenges, chief among which are the creation of consistent 3D world models and the simultaneous tracking the vehicle pose with respect to the created maps. In this paper we integrate two recently proposed algorithms in an online, near-realtime mapping and tracking system. Using the Normal Distributions Transform (NDT), a sparse Gaussian Mixture Model, for representation of 3D range scan data, we propose a frame-to-model registration and data fusion algorithm --- NDT Fusion. The proposed approach uses a submap indexing system to achieve operation in arbitrarily-sized environments. The approach is evaluated on a publicly available city-block sized data set, achieving accuracy and runtime performance significantly better than current state of the art. In addition, the system is evaluated on a data set covering ten hours of operation and a trajectory of 7.2km in a real-world industrial environment, achieving centimeter accuracy at update rates of 5-10 Hz.

Keywords: Mapping
Abstract: This paper presents an efficient method of building continuous occupancy maps using Gaussian processes for largescale environments. Although Gaussian processes have been successfully applied to map building, the applications are limited to small-scale environments due to the high computational complexity. To improve the scalability, we adopt a divide and conquer strategy where data are partitioned into manageable size of clusters and local Gaussian processes are applied to each cluster. Particularly, we propose overlapping clusters to mitigate the discontinuity problem that predictions of local estimators do not match along the boundaries. The results are consistent and continuous occupancy voxel maps in a fully Bayesian framework. We evaluate our method with simulated data and compare map accuracy and computational time with previous work. We also demonstrate our method with real data acquired from a laser range finder.

Keywords: Mapping, Localization, Intelligent Transportation Systems
Abstract: In this paper, we report a fully automated detailed mapping of a challenging urban environment using single LIDAR. To improve scan matching, extended correlative scan matcher is proposed. Also, a Monte Carlo loop closure detection is implemented to perform place recognition efficiently. Automatic recovery of the pose graph map in the presence of false place recognition is realized through a heuristic based loop closure rejection. This mapping framework is evaluated through experiments on the real world dataset obtained from NUS campus environment.

Attachments: Video Attachment
Keywords: Humanoid Robots, Biomimetics, Human-Robot Interaction
Abstract: In human skin, the ability to spatially discriminate an individual indentation from two simultaneous indentations is tailored to the need of the specific area of application on the human body. While the spatial resolution is comparatively low over wide areas of the human body, there are no insensitive spots. In addition, the measuring range is tuned to the expected loads on the respective part of the human body. Within this study these observations are utilized to solve some of the key challenges on the way towards an artificial skin as a whole-body cover for robotic systems. To enable the reliable detection of collision events which are commonly of very short duration the reaction time of the artificial skin system has to be minimized. In order to do so, the goal conflict between the required number of taxels and the required high readout frequencies has to be solved. We present the DLR approach towards scalable transduction hardware and readout electronics as a basis for the acquisition of tactile information from future whole-body covers. First experiments with prototypes of the DLR Artificial Skin demonstrate the scalability of the transduction hardware with respect to size, spatial resolution and measuring range.

Attachments: Video Attachment
Keywords: Force and Tactile Sensing, Grasping, Dexterous Manipulation
Abstract: We propose a new method for the measurement of multi-axis contact force by using vision-based fluid-type tactile sensor. The proposed sensor can also estimate the multimodal tactile information such as the slippage, the shape, the contact region and the location of the contacted object. Multi-axis contact force is transformed from the elastic membrane tensional force on the touchpad surface, and the touchpad inner pressure measured by the pressure transducer. We obtain the tensional force by solving the equilibrium equations developed in each compartmentalized segment of the membrane, based on the shape information of the touchpad. The proposed method is general and can be applied to various touchpad contact situations. The usefulness of the proposed method is demonstrated through experimental results.

Keywords: Force and Tactile Sensing, Haptics and Haptic Interfaces, Biomimetics
Abstract: In a series of papers, we have formalized an active Bayesian perception approach for robotics based on recent progress in understanding animal perception. However, an issue for applied robot perception is how to tune this method to a task, using: (i) a belief threshold that adjusts the speed-accuracy tradeoff; and (ii) an active control strategy for relocating the sensor e.g. to a preset fixation point. Here we propose that these two variables should be learnt by reinforcement from a reward signal evaluating the decision outcome. We test this claim with a biomimetic fingertip that senses surface curvature under uncertainty about contact location. Appropriate formulation of the problem allows use of multi-armed bandit methods to optimize the threshold and fixation point of the active perception. In consequence, the system learns to balance speed versus accuracy and sets the fixation point to optimize both quantities. Although we consider one example in robot touch, we expect that the underlying principles have general applicability.

Attachments: Video Attachment
Keywords: Force and Tactile Sensing, Grasping, Force Control
Abstract: Tactile sensations make grasping fragile objects a simple and unchallenging task for the human hand. Prosthetic hands lack these sensory capabilities and their users frequently struggle with such tasks. To address this problem, the benefits of compliant fingertips with contact-detection reflexes were assessed in one prosthesis user when grasping fragile objects (eggshells, foam packing peanuts, crackers, and soft clay). A commercially available myoelectric prosthetic hand was modified to include the compliant BioTac® tactile sensors (SynTouch, LLC), which have previously been demonstrated to be more sensitive to contact than the human fingertip. Upon sensing contact during hand closure on an object, the gain of the operator’s EMG command signals to the prosthesis’ motor was reduced to prevent excessive closing forces, a behavior similar to an inhibitory reflex. This allowed the prosthetic hand to quickly react to the presence of the object and permitted the operator to handle fragile objects with ease and without the usual dependency on visual feedback. The time required to grasp and move a set of fragile objects with this modified prosthesis was compared to the subject’s usual prosthetic hand. The contact detection method demonstrated both utility and reliability through faster completion times and reduced variance in the times to complete these trials.

Attachments: Video Attachment
Keywords: Force and Tactile Sensing, Grasping, Human-Robot Interaction
Abstract: In this paper, we present a tactile approach to grasp large and unknown objects, which can not be easily manipulated with a single end-effector or two-handed grasps, with the whole upper body of a humanoid robot. Instead of conventional joint level force sensing, we equip the robot with various patches of HEX-o-SKIN – a self-organizing, multi-modal cellular artificial skin. Low-level controllers, one allocated to each sensor cell, utilize a self-explored inverted jacobian-like sensory-motor map to directly transfer tactile stimulation into reactive arm motions, altering basic grasping trajectories to the need of the current object. A high-level state machine guides those low-level controllers during the different states of the grasping action. Desired contact points, and key poses for the trajectory generation, are taught through forceless tactile stimulation. First experiments on a position controlled robot, an HRP-2 humanoid, demonstrate the feasibility of our approach. Our paper contributes to the first realization of a self-organizing tactile sensor-behavior mapping on a full-sized humanoid robot, which enables: 1) a new general approach for grasping unknown objects with the whole-body; and 2) a novel way of teaching behaviors using pre-contact tactile sensing.

Keywords: Force and Tactile Sensing, Legged Robots, Micro/Nano Robots
Abstract: This work presents the design, fabrication, calibration, and testing of a multi-touch force sensor designed to measure normal ground reaction forces generated by high-speed locomotion of milli-scale legged robots. The sensor is based on the optical principle of frustrated total internal reflection (FTIR) and is capable of resolving multiple simultaneous normal forces in the range of 50 - 1000mN at a rate of 250Hz with measurement error of less than 1%. The sensor is integrated with commercial, off-the-shelf motion capture hardware and the whole system is demonstrated with a simple experiment tracking a bouncing ball and simultaneously recording kinematic state and ground reaction force data.

Keywords: Multi-Robot Coordination, Robotics in Hazardous Fields
Abstract: Despite the focus that multi-robot patrolling has received recently, there is a manifest lack of practical real-world implementations of such systems. Beyond that, the existing ones have been mainly focused on centralized policies to coordinate the team of agents. The present work addresses realistic patrol in indoor environments with teams of arbitrary number of autonomous robots performing a distributed, scalable and fault-tolerant strategy for multi-robot coordination in patrolling missions. Agents decide their actions locally and adapt to the system’s needs using distributed communication. The work is validated through experiments in a large indoor real-world environment with a team of autonomous mobile robots.

Keywords: Multi-Robot Coordination, Distributed Robot Systems
Abstract: We present a provably-good distributed algorithm for generalized task assignment problem in the context of multi-robot systems, where robots cooperate to complete a set of given tasks. In multi-robot generalized assignment problem (MR-GAP), each robot has its own resource constraint (e.g., energy constraint), and needs to consume a certain amount of resource to obtain a payoff for each task. The objective is to find a maximum payoff assignment of tasks to robots such that each task is assigned to at most one robot while respecting robots' resource constraints. MR-GAP is a NP-hard problem. It is an extension of multi-robot linear assignment problem since different robots can use different amount of resource for doing a task (due to the heterogeneity of robots and tasks). We first present an auction-based iterative algorithm for MR-GAP assuming the presence of a shared memory (or centralized auctioneer), where each robot uses a knapsack algorithm as a subroutine to iteratively maximize its own objective (using a modified payoff function based on an auxiliary variable, called price of a task). Our iterative algorithm can be viewed as (an approximation of) best response assignment update rule of each robot to the assignment of other robots at that iteration. We prove that our algorithm converges to an assignment (approximately) at equilibrium under the assignment update rule, with an approximation ratio of 1+alpha (where alpha is the approximation ratio for the Knapsack problem). We also combine our algorithm with a message passing mechanism to remove the requirement of a shared memory and make our algorithm totally distributed assuming the robots' communication network is connected. Finally, we present simulation results to depict our algorithm's performance.

Keywords: Multi-Robot Coordination
Abstract: With the introduction of multi-robot systems for exploration the question then arises, whether coordination among robots in such systems is required. We propose a model based on Markov processes to evaluate the need for coordination in multi-robot systems during the exploration of unknown environments and determine possible gains achievable through coordination. The model is illustrated by exploration of an indoor oce environment. We qualitatively identify characteristics of environments which make coordination necessary and allow to quantitatively include them in the model. The expected gain through coordination highly depends on the environment. We further investigate the impact of team sizes. In favorable environments explicit coordination is not needed at the cost of increased team sizes. This helps to raise understanding of factors having an impact on coordination functions and making it possible to approximate a possible gain through coordination.

Keywords: Multi-Robot Coordination, Redundant Robots, Motion Control
Abstract: The aim of this paper is to investigate the discretetime stability of robot motion control in the task space. The control system has been modeled as a classical inner-loop/outerloop architecture, adopted in several industrial robotic systems. The inner-loop is composed of a servo-level joint controller, and higher level kinematic feedback is performed in the outerloop. Heterogeneous dynamics is considered in the innerloop, which can for instance describe redundant coordination/ synchronization control systems with cooperative robots with non-identical dynamical responses. There are surprisingly few discrete-time stability results in the current state-of-the-art for this popular control architecture. The qualitative effects of the inner-loop dynamics on the overall stability of the system is investigated, and improved outer-loop feedback gain margins are derived.

Keywords: Multi-Robot Coordination, AI Reasoning Methods, Agent-Based Systems
Abstract: Many robotic task specifications can be naturally expressed by boolean combinations of arbitrary constraints. This allows a separation of problem description and solution strategy.

In this paper, we present a novel approach to solve non-linear constraint systems based on Satisfiability Modulo Theories.

While most SMT-based techniques emphasize completeness, we intentionally use an incomplete local search strategy. Despite this incompleteness, the presented solution is able to deal with many real world problems like task allocation or robot positioning.

We show that our approach is able to exploit the logical structure to solve highly complex tasks almost in real-time.

Keywords: Multi-Robot Coordination
Abstract: This paper presents HiDDeN, a high-level distributed architecture for multi-robot cooperation. HiDDeN aims at controlling a team of heterogeneous robots in case of uncertain communications. It relies on a mission plan defined as an instantiated HTN, i.e. a hierarchical decomposition of robots tasks. This hierarchical structure is then capitalized when we have to repair the plan after a failure detection. This repair is made as local as possible, in order to avoid unnecessary communications between robots.

Attachments: Video Attachment
Keywords: Formal Methods in Robotics and Automation, Motion and Path Planning, Reactive and Sensor-Based Planning
Abstract: A recent method to obtain correct robot controllers is to automatically synthesize them from high-level robot missions that are specified in temporal logic. In this context, we aim for controllers that are optimal, i.e., do not let the robot take unnecessarily costly paths to reach its goals. Previous work on obtaining optimal synthesized robot controllers either ignored interactions with the environment, or assumed a cooperative environment.

In this paper, we solve the problem of obtaining optimal robot controllers for adversarial environments. Our main observation is that the quality of a path to a goal has two dimensions: (1) the number of phases in which the robot waits for the environment to perform some actions and (2) the cost of the robot's actions to reach the goal. Our algorithm can take any prioritization over the possible cost combinations into account, and computes the optimal strategy in a symbolic manner, despite the fact that the action costs can be non-integer. We show the scalability of the new algorithm by example of a delivery problem.

Keywords: Sensor-based Planning, Reactive and Sensor-Based Planning, Motion and Path Planning
Abstract: This paper addresses the problem of generating the simplest plans that solve robotic planning problems. Most robotic planning algorithms are concerned with producing plans that minimize execution cost, or generalizations of such costs. Motivated by circumstances with severe computational resource limits (e.g. memory or communication constrained settings), we instead address the problem of producing concise plans. In this work, conciseness is a measure of plan size that reflects the complexity of representing the plan explicitly. We seek a plan with minimal representational size, subject to correctness and completeness. We introduce a planning algorithm that generates concise plans for planning problems that may involve both non-determinism and partial observability, and also show that finding the most concise plan is an NP-hard problem, excusing the possible sub-optimality of our algorithm's output. We describe an implementation of the algorithm, along with empirical results on the run time and solution quality for both manipulation and navigation problem domains.

Keywords: Motion and Path Planning, Planning, Scheduling and Coordination, Surveillance Systems
Abstract: We present deterministic strategies for capturing a target taking a discrete random walk on a line segment. The searcher has a limited time budget. Its goal is to maximize the probability of capturing the target within the budget. A challenging aspect of our model is that the target can cross the searcher without being captured when they take the same edge at the same time in opposite directions. We present a POMDP approach for finding the optimal search strategy, as well as an efficient approximate solution to the POMDP. The strategies found by this approach reveal structural properties of the efficient search strategies which we exploit to solve the problem efficiently without the POMDP.

Keywords: Formal Methods in Robotics and Automation, Motion and Path Planning
Abstract: In this paper, we propose a sampling-based motion planning algorithm that finds an infinite path satisfying a Linear Temporal Logic (LTL) formula over a set of properties satisfied by some regions in a given environment. The algorithm has three main features. First, it is incremental, in the sense that the procedure for finding a satisfying path at each iteration scales only with the number of new samples generated at that iteration. Second, the underlying graph is sparse, which guarantees the low complexity of the overall method. Third, it is probabilistically complete. Examples illustrating the usefulness and the performance of the method are included.

Keywords: Wheeled Robots, Collision Detection and Avoidance, Learning and Adaptive Systems
Abstract: How to find a safe and collision-free path in unstructured environments is always an important issue in mobile robotics. This paper proposed a new path planning method that exploited past experience for obstacle avoidance with a modified artificial potential field, which could help the robot avoid collisions with obstacles effectively and find the optimal path from the start to the goal. This algorithm uses case-based reasoning to obtain the available prior information of the current environment. By retrieving the past cases and adapting to the changes of the environment to solve the problem.The experiments show that this method greatly improves the performance of the robot in terms of time and distance of the path taken from the start to the target.

Keywords: Wheeled Robots, Space Robotics and Automation, Motion and Trajectory Generation
Abstract: This paper considers motion planning and control problems that are motivated by the design of tethered, extreme terrain robots. We abstract the mobility structure of these systems using a tethered differential drive robot with rimless wheels. We analyze several important issues related to this geometry. First it is shown that this vehicle cannot be modeled deterministically unless an additional degree of freedom relative to the standard differential drive vehicle is provided. The simplest kinematically consistent model is one that allows for slight prismatic motion of the axle, approximating the effects of wheel slip. We show that under mild assumptions, such a vehicle’s reachable set is dense in SE(2), implying local maneuverability. Next we study some of the constraints which the tether places on the vehicle’s motions and derive scaling laws relating wheel and vehicle speeds. Using these results, we provide simple planning and approximate path-following methods that allow tether management. In particular, we consider trajectories produced by solving an optimal control problem to minimize the integral of absolute tether-reeling rate.

Keywords: Wheeled Robots, Motion and Trajectory Generation, Nonholonomic Motion Planning
Abstract: In this paper, the path-generating regulator is extended to tracking problem along a straight passage for two-wheeled mobile robots. As most of mobile robots are with nonholonomic constraints, it is difficult for us to make them converge to the target state with a control law. To solve this problem, many methods have been proposed. One of them is Path-generating Regulator(PGR) which designs a nonlinear regulator carrying out asymptotic convergence to a given trajectory family. However, the original method is not well suited for passages. In this paper, we will present the extended PGR for the tracking problem along a straight passage. Numerical simulations and experiments are also performed to show the effectiveness of this method.

Keywords: Wheeled Robots, Motion Control
Abstract: Mobile robots with independently steerable wheels possess many high maneuverability features of omnidirectional robots while benefiting from better performance and capability of moving on rough terrains. However, motion control of such robots is a challenging task due to presence of singular configurations and unboundedly large steering velocities in the neighborhood of those singularities. Many proposed approaches rely on numerical solutions that keep the robot out of bulky regions around the singular points and hence lose some of the robot maneuverability. Based on a class of traditional path followers we design a new globally stable path following controller that exploits the high maneuverability of the platform. This design allows us to derive a set of closed-form analytical functions that describe the robot base velocity as a function of the wheels driving and steering velocities while abide to the robot non-holonomic constraints. Those functions are then utilized to find the maximum instantaneous velocity of the body that keeps the wheels velocities under the pre-specified bounds no matter how much the robot gets close or far from its singular configurations. The control algorithms developed in this paper have been evaluated on iMoro, a four wheel independently steered mobile manipulator designed and developed at IHA/TUT. Experimental data is also shown that show efficacy of the method.

Keywords: Wheeled Robots, Mechanism Design, Kinematics
Abstract: In this paper, we study the design of omnidirectional mobile robots with Active-Caster RObotic drive with BAll Transmission(ACROBAT). ACROBAT system has been developed by the authors group which realizes mechanical coordination of wheel and steering motions for creating caster behaviors without computer calculations. A motion in the specific direction relative to a robot body is fully depends on the motion of a specific motor. This feature gives a robot designer to build an omnidirectional mobile robot propelled by active-casters with no redundant actuation with a simple control. A controller of the robot becomes as simple as that for omni-wheeled robotic bases. Namely 3DOF of the omnidirectional robot is controlled by three motors using a simple and constant kinematics. ACROBAT includes a unique dual-ball transmission to transmit traction power to rotate and orient a drive wheel with distributing velocity components to wheel and steering axes in an appropriate ratio. Therefore a sensor for measuring a wheel orientation and calculations for velocity distributions are totally removed from a conventional control system. To build an omnidirectional vehicle by ACROBAT, the significant feature is some multiple drive shafts can be driven by a common motor which realizes non-redundant actuation of the robotic platform. A kinematic model of the proposed robot with ACROBAT is analyzed and a mechanical condition for realizing a non-redundant actuation is derived. Based on the kinematic model and the mechanical condition, computer simulations of the mechanism are performed. A prototype two-wheeled robot with two ACROBATs is designed and built to verify the availability of the proposed system. In the experiments, the prototype robot shows successful omnidirectional motions with a simple and constant kinematics based control.

Keywords: Wheeled Robots, Dynamics
Abstract: This paper presents the dynamic modeling and analysis of a three-wheeled omnidirectional mobile robot with MY wheels-II, whose dynamics is nonlinear and piecewise-smooth. Firstly, the detailed dynamic model of the robot is derived, which shows that the robot is actually a switched nonlinear system. Analysis of the robot dynamic properties based on the detailed dynamic model is presented in detail. Then to facilitate the controller design for the switched nonlinear system, based on the detailed dynamic model, an average dynamic model is proposed by simply averaging the wheel contact radius. The resulting average dynamic model is nonlinear and smooth, which may then be used as one solution for the model-based control design. Open-loop simulation results show the dynamic properties of the mobile robot. In addition, the effectiveness of the proposed average model in predicting characteristics of the detailed dynamic model is also illustrated through open-loop simulations.

Keywords: Wheeled Robots, Robot Safety
Abstract: In this paper, we present the tip-over prevention technique for a holonomic omnidirectional mobile robot with active dual wheel caster assemblies. The dynamical model is derived to estimate the reaction forces at each wheel in correlation to the existing dynamical properties. A tip-over prediction using the force-angle stability measure (FASM) is used to evaluate these forces and estimate the tip-over axis. A single gimbal control moment gyro (SGCMG) is proposed to counter the instability by producing a precession torque in the opposite direction of the estimated tip-over direction. Simulation results are given to demonstrate the performance of this approach.

Attachments: Video Attachment
Keywords: Adaptive Control, Physical Human-Robot Interaction, Force Control
Abstract: This paper introduces a method for estimating the constraints imposed by a human agent on a jointly manipulated object. These estimates can be used to infer knowledge of where the human is grasping an object, enabling the robot to plan trajectories for manipulating the object while subject to the constraints. We describe the method in detail, motivate its validity theoretically, and demonstrate its use in co-manipulation tasks with a real robot.

Attachments: Video Attachment
Keywords: Adaptive Control, Parallel Robots
Abstract: Cable-driven parallel robots (CDPR) are efficient manipulators able to carry heavy payloads across large workspaces. Therefore, the dynamic parameters such as the mobile platform mass and center of mass location may considerably vary. Without any adaption, the erroneous parametric estimate results in mismatch terms added to the closed-loop system, which may decrease the robot performances. In this paper, we introduce an adaptive dual-space motion control scheme for CDPR. The proposed method aims at increasing the robot tracking performances, while keeping all the cable tensed despite uncertainties and changes in the robot dynamic parameters. Reel-time experimental tests, performed on a large redundantly actuated CDPR prototype, validate the efficiency of the proposed control scheme. These results are compared to those obtained with a non-adaptive dual-space feedforward control scheme.

Attachments: Video Attachment
Keywords: Adaptive Control, Hydraulic/Pneumatic Actuators
Abstract: We introduce our Pneumatic-Electric (PE) hybrid actuator model and propose to use the model to derive a controller for the hybrid actuation system by an optimal control method. Our PE hybrid actuator is composed of Pneumatic Artificial Muscle (PAM) and an electric motor. The PE hybrid actuator is light and can generate large torque. These properties are desirable for assistive devices such as exoskeleton robots. However, to maximally take advantage of PE hybrid system, we need to reasonably distribute necessary torque to these redundant actuators by properly taking distinctive characteristics of a pneumatic actuator and an electric motor into account. To do this, in this study, we use an optimal control method called iterative LQG to reasonably distribute the necessary torque to the PAM and the electric motor. The crucial issue to apply the optimal control method to the PE hybrid system is PAM modeling. We built a PAM model composed of three elements: 1) a dynamics between air and pressure, 2) a dynamics between pressure and force, and 3) the constraint conditions. We apply our proposed method to a one degree of freedom (one-DoF) arm with PE hybrid actuator. The one-DoF arm successfully swing tasks 0.5 Hz, 2 Hz and 4 Hz and swing up and stability task by reasonably distributing necessary torque to the two different actuators in a simulated and a real environments.

Keywords: Adaptive Control, Industrial Robots
Abstract: This paper considers the problem of performing mid-ranging control of two closed-loop controlled systems which have internal saturations. The problem originates from previous work in machining with industrial robots, where an external compensation mechanism is used to compensate for position errors. Because of the limited workspace and the considerably higher bandwidth of the compensator, a mid-ranging control approach is proposed. An adaptive, model-based solution is presented, which is verified through simulations and experiments, where a close correspondence of the obtained results is achieved. Comparing the IAE of experiments using the proposed controller to previously established methods, a performance increase of up to 56 % is obtained.

Keywords: New Actuators for Robotics, Adaptive Control, Smart Actuators
Abstract: In this paper, adaptive compensation of the hysteresis in a Magneto-Rheological (MR) fluid based actuators and its application for sensor-less high fidelity force/torque control is investigated. The MR actuator considered in this paper was originally described in [1] and [2]. This actuator offers high torque-to-mass and torque-to-inertia ratios. Yet, as an essential component of MR actuators, the magnetic circuit of the actuator shows hysteresis between its input current/voltage and output magnetic field. The hysteresis in the magnetic circuit results in a similar relationship between the input current and the output torque of the MR actuator. The control scheme used with actuators possessing hysteresis often requires compensating for the hysteresis. To this end, we propose an adaptive control method based on feedback linearization that estimates both hysteresis and uncertain parameters of the magnetic circuit. A set of experiments is performed to validate the effectiveness of the proposed method.

Keywords: Hydraulic/Pneumatic Actuators, Mechanism Design, New Actuators for Robotics
Abstract: In this paper, a pneumatic power generator based on the chemical reaction is newly proposed by using a small piston pump for the injection of the fuel. Based on the understanding of chemical reaction property, the piston pump is designed by crank-slider mechanism. The piston pump allows compact size and light weight of the entire power generation system compared to the conventional approaches using blowdown tank. In order to verify the effectiveness of the proposed power generation system, we theoretically and experimentally analyze the performance of the system. In addition, we realize the power generator and applies it to an under-actuated robot finger for the feasibility test.

Keywords: New Actuators for Robotics, Joint/Mechanism, Mechanism Design
Abstract: Arctuator modules are modular actuators that provide translational motion along an arc. A motor mounted on one link of a parallelogram four-bar linkage directly drives the opposite link via a cable, gear, or friction drive. Any of the four links can be used as the base or output link, depending on whether relatively high force translational motion, relatively high motion range translational motion, or rotational motion is desired. Appropriately combining multiple modules yields devices that can provide planar or spatial translational motions. Concept designs that combine multiple Arctuator modules depict how the modules can be used for manipulation, fabrication, locomotion, and other applications. Experimental results demonstrate that a prototype Arctuator module is capable of accelerating a cantilevered load of double its own mass upward at 1 g.

Attachments: Video Attachment
Keywords: New Actuators for Robotics, Smart Actuators
Abstract: This paper reports a 2-DOF electrostatic actuator with all electrodes made with transparent materials. The actuator is composed of two plastic films, a stator film and a slider film. The two films are sectioned into four-by-four checkerboard patterns, whose squares include fine-pitched strip electrodes arranged in orthogonal directions. A pair of three-phase voltages drives the slider in open-loop, along any preset paths in the 2-D plane. A prototype was fabricated with etched indium tin oxides and screenprinted conductive polymers. With 500 V excitation, the prototype exerted 60 to 100 mN forces in eight directions, and the slider traveled along straight and circular paths within its operating range of 132 mm by 132 mm, at maximum speed of 240 mm/s. With the transparency, the actuator realizes collaboration of an actuated physical object and animated images, on surfaces of flat panel displays.

Keywords: Smart Actuators, New Actuators for Robotics, Biomimetics
Abstract: This paper presents a novel compliant differential (CD) Shape Memory Alloy (SMA) actuator with improved performance compared to traditional SMA actuators. This actuator is composed of two antagonistic SMA wires and a mechanical joint coupled with a torsion spring. The torsion spring is employed to reduce the total stiffness of SMA actuator and improve the range of motion. The antagonistic wires increase the response time as one wire can be heated up while the other wire is still in the cooling process. Dynamic model of this actuator was established for control design. Experimental results proved that this new actuator can provide larger output range of motion and faster response speed than traditional SMA actuators under the same conditions. Sine wave tracking with 0.05 Hz, 0.08 Hz and 0.1 Hz were performed and our results demonstrated that this compliant actuator has good tracking performance under simple PID control.

Attachments: Video Attachment
Keywords: Smart Actuators, Biologically-Inspired Robots, Self-Organised Robot Systems
Abstract: Nature regularly uses self-folding as an efficient approach to automated fabrication. In engineered systems, however, the use of self-folding has been primarily restricted to the assembly of small structures using exotic materials and/or complex infrastructures. In this paper we present three approaches to the self-folding of structures using low-cost, rapid-prototyped shape memory laminates. These structures require minimal deployment infrastructure, and are activated by light, heat, or electricity. We compare the fabrication of a fundamental structure (a cube) using each approach, and test ways to control fold angles in each case. Finally, for each self-folding approach we present a unique structure that the approach is particularly suited to fold, and discuss the advantages and disadvantages of each approach.

Keywords: Smart Actuators, New Actuators for Robotics, Legged Robots
Abstract: The robotic origami (Robogami) is a low-profile, sheet-like robot with multi degrees-of-freedom (DoF) that embeds different functional layers. Due to its planar form, it can take advantage of precise 2D fabrication methods usually reserved for micro and nano systems. Not only can these methods reduce fabrication time and expenses, by offering a high precision, they enable us to integrate actuators, sensors and electronic components into a thin sheet. In this research, we study sensors, actuators and fabrication methods for Robogami which can reconfigure into various forms. Our main objective is to develop technologies that can be easily applied to Robogamis consisting of many active folds and DoFs. In this paper, after studying the performance of the proposed sensors and actuators in one fold, we use a design for a crawler robot consisting of four folds to assess the performance of these technologies.

Attachments: Video Attachment
Keywords: Haptics and Haptic Interfaces, Aerial Robotics, Telerobotics
Abstract: This paper introduces a novel dynamic kinesthetic boundary to aid a pilot to navigate an aerial robotic vehicle through a cluttered environment. Classical haptic teleoperation interfaces for aerial vehicles utilize force feedback to provide the pilot with a haptic feel of the robot's interaction with an environment. The proposed approach constructs a dynamic kinesthetic boundary on the master device that provides the pilot with hard boundaries in the haptic workspace to indicate approaching obstacles. An advantage of the proposed approach is that when the vehicle is flying free of obstacles, then the haptic feedback of the joystick can be used to provide a more natural feel of the vehicle dynamics. Furthermore, rather than a gradual onset of virtual potential forces that are felt in the classical approaches, a pilot encountering the dynamic kinesthetic boundary is immediately aware of the presence of the obstacle and can act accordingly. The approach is implemented on an admittance haptic joystick to ensure that the haptic boundaries are faithfully rendered. We prove that in the case of perfect velocity tracking, the proposed algorithm will ensure the vehicle never colliding with the environment. Experiments were conducted on a robotic platform and the results provide verification of the novel approach.

Keywords: Telerobotics, Unmanned Aerial Vehicles
Abstract: This paper describes the theory and practice for a stable haptic teleoperation of a flying vehicle. It extends passivity-based control framework for haptic teleoperation of aerial vehicles in the longest intercontinental setting that presents great challenges. The practicality of the control architecture has been shown in maneuvering and obstacle-avoidance tasks over the internet with the presence of significant time-varying delays and packet losses. Experimental results are presented for teleoperation of a slave quadrotor in Australia from a master station in the Netherlands. The results show that the remote operator is able to safely maneuver the flying vehicle through a structure using haptic feedback of the state of the slave and the perceived obstacles.

Keywords: Haptics and Haptic Interfaces, Telerobotics, Human-Robot Interaction
Abstract: A novel idea for improving transparency of teleoperation systems with force feedback is presented. This approach is based on the idea of sensory subtraction presented in [12], and consists of providing the operator with independently controlled kinesthetic and cutaneous feedback to improve the realism of haptic rendering of the remote environment (i.e., transparency), while preserving stability. More specifically, cutaneous force feedback is employed to recover transparency when a lack of kinesthetic feedback has to be enforced to keep the teleoperation loop stable. The viability of this approach is demonstrated with two experiments of teleoperated needle insertion. Results showed improved performance with respect to common control techniques not employing the proposed cutaneous compensation.

Attachments: Video Attachment
Keywords: Haptics and Haptic Interfaces, Collision Detection and Avoidance
Abstract: This paper presents a disturbance observer for the sigma.7 haptic device. External torques on the haptic device links are observed to distinguish between intended user interaction and accidental collisions of the links. Collisions can be unintentional contact of the human operator, e.g. with his knee, other people accidentally getting in contact with the haptic device or objects falling on it. The observer is based on the dynamic model of the device and sensor measurements from the joint`s position sensors and an integrated force/torque sensor. Is is implemented concurrently with a control algorithm that uses the force/torque sensor to effectively reduce the inertia and friction of the sigma.7. Furthermore, forces and torques applied on the grasping unit by the human operator are observed. Experiments are done with the sigma.7 customized for the German Aerospace Center (DLR) by Force Dimension.

Keywords: Haptics and Haptic Interfaces, Telerobotics, Medical Robots and Systems
Abstract: A haptic device using flexible sheet is developed. This device elongates a rubber sheet with four servo motors in parallel. Controlling their motor angles varies softness of the sheet: stretched sheet feels hard, and loose sheet feels soft. Hence a user can feel different softness of virtual objects when he pushes the sheet directly with his finger. We apply this device to haptic feedback of real soft objects. The system consists of the haptic device and a robot with a pressure sensing device. This sensing device is a rubber hemisphere filled with air. The internal pressure is measured when the hemisphere is pressed against an object. First a user pushes the center of the sheet. The movement of the side edge of the sheet is observed with a close-up camera, and the user’s pushing pressure on the sheet is estimated. Next the robot pushes a target object so that its pushing pressure on the object, which is measured with the pressure sensing device, may coincide with the user’s pushing pressure on the sheet. At the same time, the softness of the object is estimated from the measured pushing pressure on the object and the indentation of the object, which is given by the robot’s movement. Then the haptic device controls the motor angles so that the sheet’s softness may be equal to the object’s softness. The system repeats this process in real time. In this way the user feels the same softness as the real object by pushing the sheet. As an experimental result, the developed haptic device can imitate softness of a real stuffed doll.

Attachments: Video Attachment
Keywords: Contact Modelling, Visual Servoing, Adaptive Control
Abstract: In this paper, we propose a new vision-based controller to actively deform an unknown elastic object. Note that most deformation controllers in the literature require a-priori knowledge of the object's deformation properties. In contrast to this trend, we present a new Lyapunov-based method that online estimates the unknown deformation Jacobian matrix, avoiding any model identification or calibration steps. To achieve the desired object's deformation, we derive an innovative dynamic-state feedback velocity control law using the passivity-based framework. We present a detailed experimental study to validate the feasibility of our deformation controller.

Keywords: Mobile Manipulation, Search and Rescue Robots
Abstract: Autonomous capabilities for manipulating randomly piled objects may enhance current methods of path planning and open a new field of development for mobile manipulation and Urban Search And Rescue (USAR) robotics. This paper introduces the challenge of achieving such manipulation capabilities and as a first step presents three algorithms, including a proposed novel solution, for the selection of objects to remove from a pile. The proposed algorithm determines a removability rank for each object according to the degree of its encapsulation within other objects. Using the contact vectors of the examined object, it is possible to obtain the motions that will not violate the object's unilateral contact constraints. The removability rank of the object is proportional to the union of all such motions. All algorithms were tested in simulation in full and partial knowledge modes, and evaluated on a physical robot with a simple manipulator and sensor. This work contributes: the introduction of an important autonomous manipulation challenge, the solution of which will be useful in the field of manipulation in general and USAR in particular; a specific novel algorithm for the construction of disassembly plans for piled objects; and an experimental evaluation of three algorithms targeted at such construction.

Attachments: Video Attachment
Keywords: Mobile Manipulation, Service Robots, Aerial Robotics
Abstract: This paper presents aerial manipulation using a quadrotor with a two-DOF robot arm. By considering a quadrotor and robot arm as a combined system, the kinematic and dynamic models are developed, and an adaptive sliding mode controller is designed. With the controller, an autonomous flight experiment is conducted including picking up and delivering an object, which requires simultaneous accurate control of a quadrotor and robot arm. Overall result shows that the proposed approach demonstrates satisfactory performance as a potential platform which can be utilized in various applications such as inspection, manipulation, or transportation in remote places.

Keywords: Mobile Manipulation, Animation and Simulation
Abstract: It has been demonstrated that magnetic fields are relevant for manipulating an untethered magnet, either using fixed coils or mobile permanent magnets. This paper shows however, that any magnetic manipulation method is prone to singular configurations and that the simple numerical analysis of the rank of the “manipulation matrix” is not enough to detect them. Alternatively, we propose a geometric analysis to interpret and detect the singularities as well as to decide on the acceptability of a reference trajectory. Then, we present results obtained by simulating a planar manipulation system including either multiple mobile coils or a Helmholtz like set-up.

Attachments: Video Attachment
Keywords: Mobile Manipulation, Networked Teleoperation
Abstract: This paper presents a new set of approaches for teleoperation of mobile manipulators with on-board cameras. Mobile manipulators consist of a robotic arm which provides for interaction and manipulation, and a mobile base which extends the workspace of the arm. While the position of the on-board camera is determined by the base motion, the principal control objective is the motion of the manipulator arm. This calls for intelligent control allocation between the base and the manipulator arm in order to obtain intuitive control of both the camera and the arm. We implement virtual mass-spring-damper forces between the end-effector and the camera so that the camera follows the end-effector with an overdamped characteristics. The operator therefore only needs to control the end-effector motion, while the vehicle with the camera will follow naturally. The operator is thus able to control the more than six degrees of freedom of the vehicle and manipulator through a standard haptic device. The control allocation problem, i.e., whether the vehicle or manipulator arm actuation is applied, is then performed automatically so that the operator can concentrate on manipulator motion.

Attachments: Video Attachment
Keywords: Mobile Manipulation, Motion and Trajectory Generation
Abstract: In this paper we address the problem of generating stable trajectories for a mobile manipulator on an uneven terrain in 3D. In particular we consider the problem of coordinating the motion of the manipulator and the vehicle when the manipulator is not constrained to follow any trajectory. These kinds of situations often arise in planetary exploration, where rovers equipped with a manipulator are required to navigate over general uneven terrain. Moreover the framework can also be used in situations where the mobile manipulator is required to transport objects on uneven terrain. We generate feasible trajectories for the vehicle between a given start and a goal point considering the dynamics of the manipulator. The framework proposed in the paper plans such motion profile of the manipulator that maximizes vehicle stability at each instant. A concept called Feasible Acceleration Count (FAC) is used to determine stability along a particular path. We show that, from the point of view of motion planning of mobile manipulator on uneven terrains, FAC gives a better estimate of vehicle stability than more popular metrics like Tip-Over Stability. The trajectory planner closely resembles motion primitive based graph based planning and is combined with a novel cost function derived from FAC. The efficacy of the approach is shown through simulations of a mobile manipulator system on a 2.5D uneven terrain.

Attachments: Video Attachment
Keywords: Mobile Manipulation, Visual Servoing, Marine Robotics
Abstract: This paper proposed a general framework to control underwater vehicle-manipulator systems from external sensors. The design of the control law follows several constraints and criteria to optimize the overall behavior. The task is defined in the sensor space, that is suited for visual servoing from camera or sonar images. The control input distribution between the arm and the body is considered and separated between the approach and the intervention phases. The proposed framework is validated in a realistic simulation environment, imposing constant and varying disturbances at the velocity level.

Keywords: Flexible Arms, Underactuated Robots, Hydraulic/Pneumatic Actuators
Abstract: Tendril helical motions and snake robots have a multitude of potential applications from climbing to anchoring to complex manipulation in fields such as medical, gas/oil energy, and manufacturing. Constructing a snake robot from a fluid driven, fiber reinforced elastomeric enclosure (FREE), complex helical motions are created in a lightweight, low cost, simple structure. The snake-like manipulators are created by forming a hollow cylindrical elastomer that is reinforced with two families of fibers and one additional fiber. The manipulator is then driven by changing the volume of fluid contained within, thus forming the desired helical patterns. The design of this continuum structure is analyzed for all possible fiber angles and the FREE radius. The parameters of the resulting helix including pitch and radius are determined analytically, without the need for finite element methods. Three prototypes at different points in the design space are fabricated and tested to verify the analytical model.

Attachments: Video Attachment
Keywords: Mechanism Design, Medical Robots and Systems, Surgical Robotics
Abstract: The pathway to the Maxillary sinus area is anatomically curved and narrow. Thus, using the conventional approach based on the straight-type endoscope and surgical tools, there are some limitations in inspection and treatment of the target legion of the Maxillary sinus. To cope with such problems, a dual arm robotic approach is investigated in this work for general Maxillary sinus surgery. Initially, the need for dual arm operation is explained and a compact design of the driving unit of the dual arm is proposed to insert two end-effector mechanisms into small nostril. Two 4-DOF end-effector mechanisms for acquiring the endoscopic image and performing biopsy are introduced. Next, a simple dual master device to control the motions of the two end-effector mechanisms is designed and a motion scheduling algorithm for a proper master-slave control is also developed. Finally, the feasibility of the dual master-slave system is verified through experimental work.

Keywords: Flexible Arms, Kinematics, Neural and Fuzzy Control
Abstract: In this work we address the inverse kinetics problem of a non-constant curvature manipulator driven by three cables. An exact geometrical model of this manipulator has been employed. The differential equations of the mechanical model are non-linear, therefore the analytical solutions are difficult to calculate. Since the exact solutions of the mechanical model are not available, the elements of the Jacobian matrix can not be calculated. To overcome intrinsic problems of the methods based on the Jacobian matrix, we propose for the first time a neural network learning the inverse kinetics of the soft manipulator moving in three-dimensional space. After the training, a feed-forward neural network (FNN) is able to represent the relation between the manipulator tip position and the forces applied to the cables. The results show that a desired tip position can be achieved with a degree of accuracy of 1.36% relative average error with respect to the total arm length.

Keywords: Joint/Mechanism, Medical Robots and Systems, Flexible Arms
Abstract: The next step in minimally invasive surgery is the further reduction of incisions by surgery through natural orifices (NOTES). However, physicians pointed out, that those procedures are only possible if new technologies will increase the dexterity of the instruments inside of the body. Especially the missing triangulation, the ability to manipulate tissue from two sides, needs to be obtained. This article is about the development of different Multi Snake-Like Robot Arm Kinematics to triangulate flexible endoscopic instruments at the tip of a flexible endoscope. By using selective laser sintering it is getting possible to create various shapes and designs, custom made for different patients. We are using flexure hinges and compliant mechanisms to create defined movements to perform surgery inside the human body. In the experiments, the relation between different structures and the influence of the inserted flexible endoscopic instrument are compared. The proposed kinematics are able to manipulate the flexible instruments. That proofs that SLS structures get more and more towards a use for a flexible single-port Multi Snake-Like Robot.

Keywords: Flexible Arms, Mechanism Design, Variable Stiffness Actuator Design and Control
Abstract: This paper introduces a novel grasping mechanism that combines caging and force closure approaches in order to grasp an object. The main advantage of the gripper is its adaptability to various object shapes and sizes with low DOF. The two DOF gripper takes advantage of two tendon driven trunks. Inspired from the continuum manipulator concept, the trunks do not include discrete joints and rather an elastomer plays the role of the joints. The tendon driven trunks in the first phase of grasping act as rigid links and in the second phase act as flexible mechanisms. Two prototype of the gripper are developed, tested and evaluated. The under-actuated prototypes showed a very good adaptability to different object shapes and sizes.

Keywords: Flexible Arms, Kinematics, Medical Robots and Systems
Abstract: A continuum manipulator with triangular notches is proposed for the potential medical applications, which is driven in the plane by wires embedded in bilateral symmetry channels. The focus of this present research is a mechanics-based kinematic model of the proposed continuum manipulator, which employs the Timoshenko′s beam theory to address the formulation of the manipulator bending shape. In the proposed model, the continuum manipulator is divided into several V-shape units, each of which consists of two 2-node Timoshenko beam elements. Compared with previous approaches, our proposed model discards constant curvature approximation, in which the distributed force caused by the interface contact between the wire and V-shape unit is also considered simultaneously. The proposed mechanics model is validated experimentally on a piece of Nitinol flexible manipulator, which illustrates the ability of our model to describe the continuum manipulator shape.

Keywords: Cooperating Robots, Networked Robots, Intelligent Transportation Systems
Abstract: In this paper, we attempt to develop a reusable framework of cooperative perception for vehicle control on the road that can extend perception range beyond line-of-sight and beyond field-of-view. For this goal, the following problems are addressed: map merging, vehicle identification, sensor multi-modality, impact of communications, and impact on path planning. We provide experimental results using a self-driving vehicle and manned vehicles equipped with the cooperative perception systems that we propose and implement.

Keywords: Surveillance Systems, Cooperating Robots, Multi-Robot Coordination
Abstract: This paper presents the perimeter surveillance problem using a set of cooperative robots with heterogeneous speed capabilities under communication constraints. The problem is solved using a frequency-based approach. In the proposed path-partition strategy, the robots patrol a segment length related to their own capabilities and interchanges information with its neighbors periodically. An efficient decentralized algorithm is applied to coordinate the robots from local information and decisions. Finally, simulation and experimental results are presented to illustrate the convergence and the robustness of the solution.

Attachments: Video Attachment
Keywords: Distributed Robot Systems, Swarm Robotics, Multi-Robot Coordination
Abstract: This work is developed in the framework of Institutional Robotics (IR), an approach to cooperative distributed robotic systems that draws inspiration from the social sciences. We consider a case study concerned with a swarm of simple robots which has to maintain wireless connectivity and a certain degree of spatial compactness. Robots have local, bounded communication capabilities and have to execute the task (running an IR controller) using exclusively as information their current number of wireless connections to neighbors. For the very same case study, we previously introduced an IR-based macroscopic model for the behavior of a large number of robots, validated using a submicroscopic model implemented through a realistic simulator. In this work, we go a step further and validate our submicroscopic model with real world experiments, duplicating accurately the conditions used, including a large number of robots and noisy communication channels. The main conclusions of this paper are two-fold. First, the IR approach was able to maintain the wireless connectivity of a swarm of 40 real, resource-constrained robots. This speaks in favor of the robustness and scalability of such approach. Second, the submicroscopic model implemented is faithfully capturing the reality and can be used to further optimize the performances of distributed control strategies using an IR approach.

Keywords: Autonomous Agents, Cooperating Robots, Networked Robots
Abstract: The preservation of connectivity in mobile robot networks is critical to the success of existing algorithms designed to achieve various goals. The available connectivity control algorithms mainly work through preservation of existing edges in the network. A link may be deleted if distributed decision making determines that the edge is not a cut-bridge. A controller is presented which allows edges to be broken in a continuous manner without higher-level decision making. The controller is based on maximization of the second smallest eigenvalue of the graph Laplacian. The controllers are designed for holonomic robots, and are extended for implementation on non-holonomic wheeled mobile robots. Finally, the performance of the extended controllers are demonstrated experimentally.

Attachments: Video Attachment
Keywords: Legged Robots, Distributed Robot Systems, Dynamics
Abstract: In this paper, we investigated the dynamics of a hexapod robot model whose legs are driven by nonlinear oscillators with a phase modulation mechanism including phase resetting and inhibition. This mechanism changes the oscillation period of the oscillator depending solely on the timing of the foot's contact. This strategy is based on observation of animals. The performance of the controller is evaluated using a physical simulation environment. Our simulation results show that the robot produces some stable gaits depending on the locomotion speed due to the phase modulation mechanism, which are similar to the gaits of insects.

Attachments: Video Attachment
Keywords: Distributed Robot Systems, Agent-Based Systems, Architectures, Protocols And Middle-Ware For Networked Robots
Abstract: In this paper, we consider the problem of evaluating the generic rigidity of an interconnected system in the plane, without a priori knowledge of the network's topological properties. We propose the decentralization of the pebble game algorithm of Jacobs et. al., an O(n^2) method that determines the generic rigidity of a planar network. Our decentralization is based on asynchronous inter-agent message-passing and a distributed memory architecture, coupled with consensus-based auctions for electing leaders in the system. We provide analysis of the asynchronous messaging structure and its interaction with leader election, and Monte Carlo simulations demonstrating complexity and correctness. Finally, a novel rigidity evaluation and control scenario in the accompanying media illustrates the applicability of our proposed algorithm.

Attachments: Video Attachment
Keywords: Motion and Trajectory Generation, Variable Stiffness Actuator Design and Control, Underactuated Robots
Abstract: We address the optimal control problem of robotic systems with variable stiffness actuation (VSA) including switching dynamics and discontinuous state transitions. Our focus in this paper is to consider tasks that have multiple phases of movement, contacts and impacts with the environment. By modelling such tasks as an approximate hybrid dynamical system with time-based switching, we develop a systematic methodology to simultaneously optimize control commands, stiffness profiles and temporal aspect of the movement such as switching instances and total movement duration. Numerical evaluations on a simple switching system, a realistic brachiating robot model with VSA, and a hopper with variable stiffness springs demonstrate the effectiveness of the proposed approach.

Keywords: Legged Robots, Biologically-Inspired Robots
Abstract: The ability of biological locomotors to rapidly and stably traverse unstructured environments has inspired the development of numerous legged robotic platforms. While strides have been made in negotiating terrains cluttered with obstacles, dealing with surface property variations has received less consideration. This work presents a leg stiffness control strategy that estimates the surface compliance and adjusts the leg stiffness in order to maintain a nominal locomotion behavior while allowing for stable transitions between surfaces of up to three orders of magnitude differences in ground compliance. Implementation of this technique with high-bandwidth variable stiffness actuators that are currently being developed will expand the range of legged robotic platforms to environments with sudden and significant changes in terrain characteristics.

Attachments: Video Attachment
Keywords: Legged Robots, Underactuated Robots, Mechanism Design
Abstract: Traditional 2D single-legged hoppers were able to demonstrate stable bi-directional running in a closed-loop approach. In contrast, we employ an open-loop control to achieve high-speed (0.8 m/sec or 1.78 mph) bi-directional dynamic running of the reconfigurable leg length hopper (RLLH). Our hopper has variable linear joint in series with a passive spring that allows changing its effective leg length in real-time. Furthermore by instantaneously changing the leg length at a particular amplitude and frequency. The required “thrust-forces” can be produced. We hypothesize that the direction and the speed of our hopper can be smoothly controlled by only changing the phase of the thrust-forces being applied to the ground, i.e., the change in phase between the leg-reconfiguration and the leg-oscillation. This is experimentally evaluated by varying the phase of leg-reconfiguration up-to the range of 0-2 rad (0-360 deg). Our results show a large region of a symmetric running. Moreover, a novel gait called “in-place running” is found, where the speed of running is zero. We demonstrate that by only altering the phase of applying thrust-forces together with a constant leg oscillation can robustly control the speed and transition in the direction of locomotion.

Attachments: Video Attachment
Keywords: Legged Robots, Underactuated Robots
Abstract: Bipedal robots have the potential to provide robust locomotion over uneven terrain and its dynamic stability has been shown to be analogous to that of a spring loaded inverted pendulum (SLIP). The SLIP model is fundamentally limited in its ability to accurately represent legged locomotion since it does not take into account the impulsive dynamics of foot ground interaction. In this paper we investigate the control of a four-link hopping robot based on the complete dynamics of the system. Using partial feedback linearization to control the configuration in continuous time, and discrete parameter variations the control object of apex height control of the robot is achieved. Simulation results are presented to show the efficacy of the control scheme.

Keywords: Legged Robots, Motion Control, Compliance and Impedance Control
Abstract: Bouncing, balancing and swinging the leg forward can be considered as three basic control tasks for bipedal locomotion. Defining the trunk by an unstable inverted pendulum, balancing as being translated to trunk stabilization is the main focus of this paper. The control strategy is to generate a hip torque to have upright trunk to achieve robust hopping and running. It relies on the Virtual Pendulum (VP) concept which is recently proposed for trunk stabilization, based on human/animal locomotion analysis. Based on this concept, a control approach, named Virtual Pendulum Posture control (VPPC) is presented, in which the trunk is stabilized by redirecting the ground reaction force to a virtual support point. The required torques patterns generated by the controller, could partially be exerted by elastic structures like hip springs. Hybrid Zero Dynamics (HZD) control approach is also applied as an exact method of keeping the trunk upright. Stability of the motion which is investigated by Poincar´e map analysis could be achieved by hip springs, VPPC and HZD. The results show that hip springs, revealing muscle properties, could facilitate trunk stabilization. Compliance in hip produces acceptable performance and robustness compared with VPPC and HZD, while it is a passive structure.

Attachments: Video Attachment
Keywords: Humanoid and Bipedal Locomotion, Humanoid Robots, Motion and Trajectory Generation
Abstract: This paper presents new methods to control high-speed running in a simulated humanoid robot at speeds of up to 6.5 m/s. We present methods to generate compliant target CoM dynamics through the use of a 3D spring-loaded inverted pendulum (SLIP) template model. A nonlinear least-squares optimizer is used to find periodic trajectories of the 3D-SLIP offline, while a local deadbeat SLIP controller provides reference CoM dynamics online at real-time rates to correct for tracking errors and disturbances. The local deadbeat controller employs common foot placement strategies that are automatically generated by a local analysis of the 3D-SLIP apex return map. A task-space controller is then applied online to select whole-body joint torques which embed these target dynamics into the humanoid. Despite the body of work on the 2D and 3D-SLIP models, to the best of the authors' knowledge, this is the first time that a SLIP model has been embedded into a whole-body humanoid model. When running at 3.5 m/s, the controller is shown to reject lateral disturbances of 40 N s applied at the waist. A final demonstration shows the capability of the controller to stabilize running at 6.5 m/s, which is comparable with the speed of an Olympian in the 5000 meter run.

Keywords: Mapping
Abstract: In this paper, we propose a generalizable method that systematically combines data driven MCMC sampling and inference using rule-based context knowledge for data abstraction. In particular, we demonstrate the usefulness of our method in the scenario of building abstract semantic maps for indoor environments. The product of our system is a parametric abstract model of the perceived environment that not only accurately represents the geometry of the environment but also provides valuable abstract information which benefits high-level robotic applications. Based on predefined abstract terms, such as “type” and “relation”, we define task-specific context knowledge as descriptive rules in Markov Logic Networks. The corresponding inference results are used to construct a prior distribution that aims to add reasonable constraints to the solution space of semantic maps. In addition, by applying a semantically annotated sensor model, we explicitly use context information to interpret the sensor data. Experiments on real world data show promising results and thus confirm the usefulness of our system.

Keywords: Mapping, Field Robots, Sensor Fusion
Abstract: Operating in vegetated environments is a major challenge for autonomous robots. Obstacle detection based only on geometric features causes the robot to consider foliage, for example, small grass tussocks that could be easily driven through, as obstacles. Classifying vegetation does not solve this problem since there might be an obstacle hidden behind the vegetation. In addition, dense vegetation typically needs to be considered as an obstacle. This paper addresses this problem by augmenting probabilistic traversability map constructed from laser data with ultra-wideband radar measurements. An adaptive detection threshold and a probabilistic sensor model are developed to convert the radar data to occupancy probabilities. The resulting map captures the fine resolution of the laser map but clears areas from the traversability map that are induced by obstacle-free foliage. Experimental results validate that this method is able to improve the accuracy of traversability maps in vegetated environments.

Keywords: Mapping, Range Sensing, Sensor-based Planning
Abstract: In this paper we examine the correlation between the information content and the spatial realization of range measurements taken by a mapping robot. To do so, we consider the task of constructing an occupancy grid map with a binary Bayesian filter. Using a narrow beam-based sensor model (versus an additive white Gaussian noise model), we prove that any controller tasked to maximize a mutual information reward function is eventually attracted to unexplored space. This intuitive behavior is derived solely from the geometric dependencies of the occupancy grid mapping algorithm and the monotonic properties of mutual information. Since it is a function of both the robot's position and the uncertainty of the surrounding cells, mutual information encodes geometric relationships that are fundamental to robot control, thus yielding geometrically relevant reward surfaces on which the robot can navigate. Lastly, we present the results of two experiments employing an omnidirectional ground robot equipped with a laser rangefinder.

Attachments: Video Attachment
Keywords: Mapping, Humanoid Robots, Mobile Manipulation
Abstract: Without a precise and up-to-date model of its environment a humanoid robot cannot move safely or act usefully. Ideally, the robot should create a dense 3D environment model in real-time, all the time, and respect obstacle information from it in every move it makes as well as obtain the information it needs for fine manipulation with its fingers from the same map.

We propose to use a multi-scale truncated signed distance function (TSDF) map consisting of concentric, nested cubes with exponentially decreasing resolution for this purpose. We show how to extend the KinectFusion real-time SLAM algorithm to the multi-scale case as well as how to compute a multi-scale Euclidean distance transform (EDT) thereby establishing the link to optimization-based planning.

We overcome the inability of KinectFusion's localization to handle scenes without enough constraining geometry by switching to mapping-with-known-poses based on forward kinematics. The latter is always available and we know when it is precise. The resulting map has the desired properties: It is computed in real-time (7.5ms per depth frame for a (8m)^3 multi-scale TSDF volume), covers the entire laboratory, does not depend on scene properties (geometry, texture, etc.) and is precise enough to facilitate grasp planning for fine manipulation tasks - all in a single map.

Keywords: Mapping, Localization, SLAM
Abstract: This paper presents a map-merging method which builds a 3-D visual map by connecting part maps. The purpose is to increase flexibility and robustness in 3-D mapping. Map merging is performed by combining image retrieval using bag-of-words, geometric verification, and pose adjustment. A key issue is robust data association. To cope with false matches, we perform group matching with pose propagation, which checks the geometric consistency of point correspondences over multiple frames. Also, we perform path consistency check, which examines the accumulated errors along a loop to eliminate inconsistent part map connections. Experiments show our method successfully built detailed 3-D maps of indoor environments.

Keywords: Mapping, Visual Navigation, Field Robots
Abstract: We present a vision-based mapping and localization system for operations in pipes such as those found in Liquified Natural Gas (LNG) production. A forward facing fisheye camera mounted on a prototype robot collects imagery as it is tele-operated through a pipe network. The images are processed offline to estimate camera pose and sparse scene structure where the results can be used to generate 3D renderings of the pipe surface. The method extends state of the art visual odometry and mapping for fisheye systems to incorporate geometric constraints based on prior knowledge of the pipe components into a Sparse Bundle Adjustment framework. These constraints significantly reduce inaccuracies resulting from the limited spatial resolution of the fisheye imagery, limited image texture, and visual aliasing. Preliminary results are presented for datasets collected in our fiberglass pipe network which demonstrate the validity of the approach.

Attachments: Video Attachment
Keywords: Sensor Fusion, Computer Vision
Abstract: The paper concerns visuo-inertial filtering and estimation based on homography and angular velocity measurements, i.e. data obtained from a mono-camera/IMU sensor. We extend recently developed nonlinear filters on the special linear group of homographies to the estimation of scene parameters and velocity of the sensor. A validation of the proposed solution and a comparative evaluation based on real data is presented.

Keywords: Sensor Fusion, Range Sensing, Unmanned Aerial Vehicles
Abstract: For the purpose of autonomous UAV flight control, cameras are ubiquitously exploited as a cheap and effective onboard sensor for obtaining non-metric position or velocity measurements. Since the metric scale cannot be directly recovered from visual input only, several methods have been proposed in the recent literature to overcome this limitation by exploiting independent `metric' information from additional onboard sensors. The flexibility of most approaches is, however, often limited by the need of constantly tracking over time a certain set of features in the environment, thus potentially suffering from possible occlusions or loss of tracking during flight. In this respect, in this paper we address the problem of estimating the scale of the observed linear velocity in the UAV body frame from direct measurement of the instantaneous (and non-metric) optical flow, and the integration of an onboard Inertial Measurement Unit (IMU) for providing (metric) acceleration readings. To this end, two different estimation techniques are developed and critically compared: a standard Extended Kalman Filter (EKF) and a novel nonlinear observer stemming from the adaptive control literature. Results based on simulated and real data recorded during a quadrotor UAV flight demonstrate the effectiveness of the approach.

Attachments: Video Attachment
Keywords: Sensor Fusion, Recognition
Abstract: This paper presents a method for detecting moving entities that are in the robot’s path but are not in the field of view of sensors like lasers, cameras or ultrasonic sensors. The proposed system makes use of passive acoustic localization methods which receive information from occulded regions (at intersections or corners) because of the multipath nature of sound propagation. Contrary to the conventional sensors, this method does not require line of sight. In particular, specular reflections in the environment make it possible to detect moving entities that emit sound such as a walking person or a rolling cart. This idea was exploited for safe navigation of a mobile platform at intersections. The passive acoustic localization output is combined with a 3D geometric map of the environment that is precise enough to estimate sound propagation and reflection using ray casting methods. This gives the robot the ability to detect a moving entitiy out of the field of view of the sensors that require line of sight. Then the robot is able to re-calculate its path and waits until the detected entity is out of its path so that it is safe to move to its destination. To illustrate the performance of the proposed method, a comparison of the robot’s navigation with and without the audio sensing is provided for several intersection scenarios.

Keywords: Sensor Fusion, Localization, Range Sensing
Abstract: This paper presents a new approach to fuse 3D and 2D information in a driver assistance setup, in particular to perform obstacle detection and tracking. We propose a new cooperative fusion method between two exteroceptive sensors: it is able to address highly non linear dynamic configuration without any assumption on the driving maneuver. Information are provided by a mono-layer laser scanner and a monocular camera which are unsynchronized. The initial detection stage is performed using the 1D laser data, which computes clusters of points which might correspond to vehicles present on the road. These clusters are projected to the image to define targets, which will be tracked using image registration techniques. This multi-object association and tracking scheme is implemented using belief theory integrating temporal and spatial information, which allows the estimation of the dynamic state of the tracks and to monitor appearance and disappearance of obstacles. Accuracy of the method is evaluated on a database made publicly available, focus is cast on the relative localization of the vehicle ahead: estimations of its longitudinal and lateral distances are analysed.

Keywords: Sensor Fusion, Computer Vision, Computer-assisted diagnosis and therapy
Abstract: Keyframe selection is the process of finding a representative frame in an image sequence. Although mostly known from video processing, keyframe selection faces new challenges in the lifelog domain. To obtain a keyframe that is close to a user-selected frame, we propose a keyframe selection method based on image quality measurements and excitement features. Image quality measurements such as contrast, color variance, sharpness, noise and saliency are used to filter high quality images. However, high quality images are not necessarily keyframes because humans also use emotions in the selection process. In this study, we employ a biosensor to measure the excitement of humans. In previous investigation, keyframe selection using only image quality measurements yielded an acceptance rate of 79.70 %. Our proposed method achieves an acceptance rate of 84.45 %.

Keywords: Sensor Fusion, Learning and Adaptive Systems, Unmanned Aerial Vehicles
Abstract: The fusion of multi-sensor information for state estimation is a well studied problem in robotics. However, the classical methods may fail to take into account the measurements validity, therefore ruining the benefits of sensor redundancy. This work addresses this problem by learning context-dependent knowledge about sensor reliability. This knowledge is later used as a decision rule in the fusion task in order to dynamically select the most appropriate subset of sensors. For this purpose we use the Mixture of Experts framework. In our application, each expert is a Kalman filter fed by a subset of sensors, and a gating network serves as a mediator between individual filters, basing its decision on sensor inputs and contextual information to reason about the operation context. The performance of this model is evaluated for altitude estimation of a UAV.

Keywords: Multi-Robot Coordination, Cooperative Manipulators, Path Planning for Multiple Mobile Robots or Agents
Abstract: Cooperative manipulation, where several robots collaboratively transport an object, poses a great challenge in robotics. In order to avoid object deformations in cooperative manipulation, formation rigidity of the robots is desired. This work proposes a novel linear state feedback controller that combines both optimal goal regulation and a relaxed form of the formation rigidity constraint, exploiting an underlying distributed impedance control scheme. Since the presented control design problem is in a biquadratic LQR-like form, we present an iterative design algorithm to compute the controller. As an intermediate result, an approximated state-space model of an interconnected robot system is derived. The controller design approach is evaluated in a full-scale multi-robot experiment.

Attachments: Video Attachment
Keywords: Multi-Robot Coordination, Navigation, Autonomous Agents
Abstract: In this paper, we combine navigation functions and constraint based programming to achieve obstacle avoidance in formation. Constraint based programming was developed in robotic manipulation as a technique to take several constraints into account when controlling redundant manipulators. The approach has also been generalized, and applied to other control systems such as dual arm manipulators and unmanned aerial vehicles. Navigation functions are a very elegant way to design controllers with provable properties for navigation problems. By combining these tools, we take advantage of the redundancy inherent in a multi agent control problem and are able to concurrently address features such as formation maintenance and goal convergence, even in the presence of moving obstacles. We show how the user can decide a priority ordering of the objectives, as well as a clear way of seeing what objectives are currently addressed and what are postponed. We also analyze controller properties which can be guaranteed under different circumstances. Finally, we use a set of simulations to illustrate the approach.

Attachments: Video Attachment
Keywords: Multi-Robot Coordination, Cooperating Robots
Abstract: We are interested in forming a multi-robot team that attains high utility at a task, and is robust to failures in the robots. We consider configurable robots that are composed of modules, e.g., motors, sensors, and actuators, where each module has an independent probability of failure. The performance of the multi-robot team at the task depends not only on how the robots in the team are composed from modules, but also the probability of failure of the selected modules. We formally define the robust team formation problem, and introduce two methods of defining the optimal team. We contribute the Robust Synergy Graph for Configurable Robots (rho-SGraCR) model, and two team formation algorithms to find effective robust teams. The first algorithm, OptRobust, runs in exponential time and finds the optimal robust team. The second algorithm, ApproxRobust, makes assumptions about the module failures and approximates the optimal robust team, and runs in polynomial time. We demonstrate the efficacy of the rho-SGraCR model in modeling robust team performance, and evaluate ApproxRobust and OptRobust. Finally, we apply the rho-SGraCR model to a real robot problem in the foraging domain, and show that it outperforms competing approaches.

Keywords: Multi-Robot Coordination, Cooperating Robots, Learning and Adaptive Systems
Abstract: In many multi-robot problems, the performance of a team of robots is not the sum of their individual capabilities; there is often synergy among the robots. We recently introduced the synergy graph model to model such phenomena, where robots are represented by vertices in a graph, their capabilities represented by Normally-distributed variables, and the interactions of robots represented with the structure of the graph. The synergy graph is learned from observations of robot team performances, with the underlying assumption that observations of all the robots are available at once. However, it is common that new information becomes available over time, in particular as new robots enter the domain. In this paper, we contribute a learning algorithm that uses new information to add a new robot into an existing synergy graph, that requires a smaller number of observations and faster computation than relearning the entire synergy graph using the existing learning algorithms. We introduce three heuristics to initialize the learning algorithm, and perform extensive simulations to analyze their characteristics, as well as compare two methods of learning robot capabilities, over a variety of graph structure types. We also compare three approaches to learning synergy graphs, and demonstrate that adding a new teammate into an existing synergy graph introduces higher error than completely relearning the synergy graph. However, it is computationally less expensive to add a new teammate, especially when the number of robots is large.

Attachments: Video Attachment
Keywords: Multi-Robot Coordination, Human-Robot Interaction, Computer Vision
Abstract: This paper addresses the issue of human-swarm interactions by proposing a new set of affordances that make a multi-robot system amenable to human control. In particular, we propose to use clay -- a deformable medium -- as the "joystick" for controlling the swarm, supporting such affordances as stretching, splitting and merging, shaping, and mixing. The contribution beyond the formulation of these affordances is the coupling of an image recognition framework to decentralized control laws for the individual robots, and the developed human-swarm interaction methodology is applied to a team of mobile robots.

Attachments: Video Attachment
Keywords: Cooperating Robots, Distributed Robot Systems, Search and Rescue Robots
Abstract: We propose a map merging algorithm that is capable of merging together heterogeneous maps independently built by different robots. Heterogeneous map merging is a crucially important problem for scenarios where multiple heterogeneous robots collaborate to provide situational awareness in urban search and rescue, patrolling, and explorations tasks, just to name a few. To remedy the lack of uniform representation between heterogeneous map models, we rely on the ubiquitous presence of WiFi signals in today's environments. Our solution consists of three steps. First, the overlap between the heterogeneous maps being merged is determined. Second, metric correspondences between overlapping parts are established. Third, the merging is improved by exploiting the structural properties inherent to graph-based maps. Our proposed system is validated using various occupancy grid and appearance-based maps built in real-world conditions, the results of which confirm its strengths. To the best of our knowledge, this is the first solution to the heterogeneous map merging problem.

Attachments: Video Attachment
Keywords: Sensor-based Planning, Perception for Grasping and Manipulation, Domestic Robots and Home Automation
Abstract: Robotic environment exploration in cluttered environments is a challenging problem. The number and variety of objects present not only make perception very difficult but also introduce many constraints for robot navigation and manipulation. In this paper, we investigate the idea of exploring a small, bounded environment (eg. the shelf of a home refrigerator) by prehensile and non-prehensile manipulation of the objects it contains. The presence of multiple objects results in partial and occluded views of the scene. This inherent uncertainty in the scene's state forces the robot to adopt an observe-plan-act strategy and interleave planning with execution. Objects occupying the space and potentially occluding other hidden objects are rearranged to reveal more of the unseen area. The environment is considered explored when the state (free or occupied) of every voxel in the volume is known. The presented algorithm can be easily adapted to real world problems like object search, taking inventory, and mapping. We evaluate our planner in simulation using various metrics like planning time, number of actions required, and length of planning horizon. We then present an implementation on the PR2 robot and use it for object search in clutter.

Keywords: Path Planning for Manipulators, Reactive and Sensor-Based Planning, Visual Navigation
Abstract: In this paper, we propose a SPAM (Simultaneous Planning and Mapping) technique for a manipulator type robot working in an uncertain environment via a Best Next Move algorithm. Demands for a smart decision to move a manipulator such as humanoid arms in uncertain or crowded environments call for a simultaneous planning and mapping technique. We assume no a priori knowledge of either the obstacles or the rest of the environment exits. For rapid map building and path planning, we use a 3D depth camera based skin type sensors setup that completely encompass the entire body of a manipulator. Captured cloud points by 3D sensors create an instantaneous c-space map whereby a Best Next Move algorithm directs the motion of the manipulator. The Best Next Move algorithm utilizes the gradient of the density distribution of the k-nearest-neighborhood sets in c-space. It has tendency to travel along the direction by which the point clouds spread in space, thus rendering faster mapping of c-space obstacles.

Proposed algorithm is compared with several sensor based algorithms for performance measure such as map completion rate, distribution of samples, total nodes, etc. Improved performances are reported for the proposed algorithm. Possible applications include semi-autonomous tele-robotics planning, humanoid arm path planning, among others.

Keywords: Formal Methods in Robotics and Automation, Task Planning, Navigation
Abstract: In this paper, we consider a robot motion planning problem from a specification given as a syntactically co-safe linear temporal logic formula over a set of properties known to be satisfied at the regions of an unknown environment. The robot is assumed to be equipped with deterministic motion and accurate sensing capabilities. The environment is assumed to be partitioned into a finite number of identical square cells. By bringing together tools from formal verification, graph theory, and grid-based exploration, we develop an incremental algo- rithm that makes progress towards satisfying the specification while the robot discovers the environment using its local sensors. We show that the algorithm is sound and complete. We illustrate the feasibility and effectiveness of our approach through a simulated case study.

Keywords: Planning, Scheduling and Coordination, AI Reasoning Methods, Sensor-based Planning
Abstract: Recent advances in navigation and control of robots has increasingly led to systems where the actions are deterministic and the challenge is to collect information about the world using noisy sensors. Examples include search and rescue, Mars rover planning and robotic monitoring tasks. However, theoretical results show that in general these problems are as hard as solving partially observable Markov decision problems (POMDPs). We propose an approach where we build plans assuming both the actions and the observations are reliable, then monitor the execution of the plan and use a value of information calculation to add information gathering actions on-line. We describe two variants: one using a classical contingency planner to generate the initial plan, and the other using a Markov decision problem planner. We show how in both cases the addition of execution monitoring can considerably improve overall performance with lower computational cost than solving the original POMDP.

Keywords: Formal Methods in Robotics and Automation, Performance Evaluation and Benchmarking, Behaviour-Based Systems
Abstract: Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behavior-based controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.

Keywords: Motion and Path Planning, Path Planning for Manipulators, Mobile Manipulation
Abstract: In this paper, the authors proposed a local motion planner with robot controller of the mobile manipulator to grasp the object in dynamic environments without any prior knowledge of environments. Our local motion planner is based on the concept of potential field and composed of the attractive and repulsive vectors. Then, the local motion planner decides the potential vector according to the attractive and repulsive vectors in various situations. Also, an approach to deal with the drawback of local minima is contained. The attractive and repulsive vectors are generated by the distances between the target, obstacles and the manipulator. For robot control, we take the end-effector as the control point and apply the potential vector with joint-level control, and moreover evaluate the mobility and the kinematic constraints of the robot to modify the joint velocities. The experiment platform is a wheeled mobile robot with a 5-DOF manipulator using Softkinetic DS325 which is a close range RGB-D camera as our sensor. Through several experiments, the results show that our framework is fast enough and valid to grasp the object in dynamic environments.

Keywords: Robotics in Agriculture and Forestry, Navigation
Abstract: Rows of trees such as in orchards, planted in straight parallel lines can provide navigation cues for autonomous machines that operate in between them. When the tree canopies are well managed, tree rows appear similar to corridor walls and a simple 2D sensing scheme suffices. However, when the tree canopies are three dimensional, or ground vegetation occludes tree trunks, it is necessary to use a three dimensional sensing mode. An additional complication in prolific canopies is that GPS is not reliable and hence is not suitable to register data from sensors onboard a traversing vehicle. Here, we present a method to register 3D data from a lidar sensor onboard a vehicle that must accurately determine its pose relative to the rows. We first register point cloud into a common reference frame and then determine the position of tree rows and trunks in the vicinity to determine the vehicle pose. Our method is tested online and with data from commercial orchards. Experimental results show that the accuracy is sufficient to enable accurate traversal between tree rows even when tree canopies do not approximate planar walls.

Keywords: Robotics in Agriculture and Forestry, Field Robots, Computer Vision
Abstract: This paper presents a multi-class image segmentation approach to automate fruit segmentation. A feature learning algorithm combined with a conditional random field is applied to multi-spectral image data. Current classification methods used in agriculture scenarios tend to use hand crafted application-based features. In contrast, our approach uses unsupervised feature learning to automatically capture most relevant features from the data. This property makes our approach robust against variance in canopy trees and can therefore be applied to different domains. The proposed algorithm is applied to a fruit segmentation problem for a robotic agricultural surveillance mission, aiming to provide yield estimation with high accuracy and robustness against fruit variance. Experimental results with data collected in an almond farm as shown. The segmentation is performed with features extracted from multi-spectral (colour and infrared) data. We achieve a global classification accuracy of 88%.

Keywords: Robotics in Agriculture and Forestry, Path Planning for Multiple Mobile Robots or Agents, Sensor Networks
Abstract: We study the problem of coordinating an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) for a precision agriculture application. In this application, the ground and aerial measurements are used for estimating nitrogen (N) levels on-demand across a farm. Our goal is to estimate the N map over a field and classify each point based on N deficiency levels. These estimates in turn guide fertilizer application. Applying the right amount of fertilizer at the right time can drastically reduce fertilizer usage.

Towards building such a system, this paper makes the following contributions: First, we present a method to identify points whose probability of being misclassified is above a threshold. Second, we study the problem of maximizing the number of such points visited by an UAV subject to its energy budget. The novelty of our formulation is the capability of the UGV to mule the UAV to deployment points. This allows the system to conserve the short battery life of a typical UAV. Third, we introduce a new path planning problem in which the UGV must take a measurement within a disk centered at each point visited by the UAV. The goal is to minimize the total time spent in traveling and measuring. For both problems, we present constant-factor approximation algorithms. Finally, we demonstrate the utility of our system with simulations which use manually collected soil measurements from the field.

Keywords: Mining and Demining, Robotics in Hazardous Fields, Manipulation Planning and Control
Abstract: Humanitarian demining aims at clearing landmine affected areas, but the current manual demining techniques are still slow, costly and dangerous. Discrimination methods for distinguishing between real mines and metal fragments would greatly increase efficiency of such demining operations, but none practical solution has been implemented yet. Important information for discrimination are the depth which targets are buried and the material they are made, so estimation methods of these properties are desired. In this research, a new, accurate and fast method for estimating metallic targets depth using Metal Mine Detectors is presented, which takes advantage of high precision scanning of the minefield using robotic manipulator.

Keywords: Search and Rescue Robots, Human-Robot Interaction, Architectures, Protocols And Middle-Ware For Networked Robots
Abstract: Urban search and rescue (USAR) missions are unique and unpredictable. Communication and coordination is difficult, with high-level actors (e.g. mission commander) lacking local terrain knowledge while low-level actors (e.g. robot operators, in-field rescuers) lack global situation awareness (SA). In-field actors have high mobility and a direct view of the field, but so far they could communicate this SA almost exclusively through radio. Unfortunately, words are imprecise and unorganized, and thus not easily analyzable and retrievable.

As part of the NIFTi project, we performed high-fidelity USAR simulations and missions at fire fighting training sites and disaster areas. We developed mobile applications to help infield actors share their SA with the rescue team. We discovered a need for persistent geo-localized information and propose a novel system architecture that integrates pictures taken from robots and from in-field rescuers into the existing systems at the command post.

Attachments: Video Attachment
Keywords: Industrial Robots, Field Robots, Education Robotics
Abstract: In recent decades, the devastating earthquakes, which can damage a lot of houses and buildings, have frequently happened. To slow down or prevent the disastrous damages of the earthquake, the various technologies have been required. Of these technologies, the ground motion simulator of the earth-quake is used to alert people to the dangers of the earthquake. This paper introduces a potable earthquake simulator, called a Jishin-The-Vuton 3D, which realizes the up-and-down motion with the holonomic omni-directional motions in order to simulate three-dimensional ground motion of the earthquake. Focusing on the design concept, structure, and feature of this new simulator, the authors discuss its implementation and verify its feasibility with preliminary experimental results.

Keywords: Collision Detection and Avoidance, Motion and Path Planning
Abstract: We present a fast, yet accurate k-nearest neighbor search algorithm for high-dimensional sampling-based motion planners. Our technique is built on top of Locality Sensitive Hashing (LSH), but is extended to support arbitrary distance metrics used for motion planning problems and adapt irregular distributions of samples generated in the configuration space. To enable such novel characteristics our method embeds samples generated in the configuration space into a simple l2 norm space by using pivot points. We then implicitly define Voronoi regions and use local LSHs with varying quantization factors for those Voronoi regions. We have applied our method and other prior techniques to high-dimensional motion planning problems. Our method is able to show performance improvement by a factor of up to three times even with higher accuracy over prior, approximate nearest neighbor search techniques.

Attachments: Video Attachment
Keywords: Collision Detection and Avoidance, Industrial Robots, Animation and Simulation
Abstract: Cylinder, a common geometric entity has a discontinuity at the joining of cylindrical surface and circular-disks. Hence, collision detection between two cylinders in space is a difficult task and few have reported formulations to solve it. In this paper, a novel analytical methodology is proposed to detect collision or intersection between two cylinders. The configuration, i.e., position and orientation, between the cylinders was represented using the four Denavit-Hartenberg (DH) parameters plus two extra parameters. Dual Number Algebra was used to extract these six parameters. Tests involved in collision detection between the cylinders were between the lines and rectangles in a plane, thus considerably simplifying the problem of collision detection. As an illustration, an one-DOF arm modeled as a cylinder with cylindrical shaped obstacles were modeled and tested for their collisions. The results were validated with an analytical method available in the literature and a commercial software

Attachments: Video Attachment
Keywords: Collision Detection and Avoidance, Surveillance Systems, Robot Safety
Abstract: This paper presents the application of a novel projection-based safety system for ensuring hard safety in human-robot collaboration. We adapted the proposed sensor system to incorporate the joint positions and velocities of a collaborative robot, thus offering the opportunity to establish minimal and well-shaped safety spaces around the robot at any time. In this contribution we explain in detail main challenges and their solutions for generating and monitoring such safety spaces. Furthermore, we build up a future collaborative workplace to demonstrate the practicability of the system under operational conditions.

Keywords: Collision Detection and Avoidance, Motion and Path Planning, Manipulation Planning and Control
Abstract: This paper presents an adaptive algorithm for checking collisions over any continuous robot motion set when tasks or constraints are given. As robots have begun to operate in human environments, which are unstructured and dynamically changing, the need for on-line robot planning and control strategies has increased. In implementing an on-line system, a fast and reliable collision checking method for continuous paths is a critical element. However, since external objects move unexpectedly, collision checking along the continuous path of a robot’s motion suffers from increased uncertainty. Furthermore, computing the desired motion path or trajectory of a complex robotic task is very complex and slow. Therefore, we have developed a new collision checking strategy that can be applied to many types of motions that satisfy many given constraints. Our algorithm defines the applicable robot motions in a constraint-based manner, which is suitable for the multiple task motion of a complex robot. This method can check the collision for the entire motion by finding the worst case with a small amount of computation, so that we can use the method for on-line applications. Moreover, our algorithm has a feature of adaptive resolution, which provides advantages in dynamically changing environments. The proposed method has been tested on high d.o.f. robots and the experimental results show that the method is suitable for on-line applications of multiple-tasks.

Attachments: Video Attachment
Keywords: Collision Detection and Avoidance, Human-Robot Interaction, Motion and Trajectory Generation
Abstract: All mammals but humans use whiskers in order to rapidly acquire information about objects in the vicinity of the head. Collisions of the head and objects can be avoided as the contact point is moved from the body surface to the whiskers. Such a behavior is also highly desirable during many robot tasks such as for human-robot interaction. Using novel capacitive proximity sensors, robots sense when they approach a human (or an object) and react before they actually collide with it. We propose a sensor and control concept that mimics the behavior of whiskers by means of capacitive sensors. Major advantages are the absence of physical whiskers, the absence of blind spots and a very short response time. The sensors are flexible and thin so that they feature skin-like properties and can be attached to various robotic link and joint shapes. In comparison to capacitive proximity sensors, the proposed virtual whiskers offer better sensitivity towards small conductive as well as non conductive objects. Equipped with the new proximity sensors, a seven-joint robot for humanrobot interaction tasks shows the efficiency and responsiveness of our concept.

Keywords: Collision Detection and Avoidance, Motion and Trajectory Generation, Human-Robot Interaction
Abstract: The ability of the robot to avoid undesired collisions with humans and objects in its workspace is of importance in the field of human-robot interaction. In this paper, we propose an algorithm which allows the robot to avoid obstacles and to reach the assigned goal as long as the goal does not lie within obstacles. For this purpose, dynamical system modulation approach is adopted which ensures the avoidance of convex and concave obstacles. A modulation matrix can be calculated directly from the point cloud data of obstacles in the scene, without the need of analytical representation of the obstacles. This matrix modulates a generic first order dynamical system, used to generate the goal. In this way we guarantee the obstacles avoidance and the reaching of the goal. The effectiveness of the proposed approach is validated with numerical simulations and experiments on a 7 DOF KUKA light weight arm.

Attachments: Video Attachment
Keywords: Variable Stiffness Actuator Design and Control, Legged Robots, Adaptive Control
Abstract: Compliant actuators in robotic systems improve robustness against rigid impacts and increase the performance and efficiency of periodic motions such as hitting, jumping and running. However, in the case of rigid impacts, as they can occur during hitting or running, the system behavior is changed compared to free motions which turns the control into a challenging task. We introduce a controller that excites periodic motions along the direction of an intrinsic mechanical oscillation mode. The controller requires no model knowledge and adapts to a modal excitation by means of measurement of the states. We experimentally show that the controller is able to stabilize a hitting motion on the variable stiffness robot DLR Hand Arm System. Further, we demonstrate by simulation that the approach applies for legged robotic systems with compliantly actuated joints. The controlled system can approach different modes of motion such as jumping, hopping and running, and thereby, it is able to handle the repeated occurrence of robot-ground contacts.

Keywords: Variable Stiffness Actuator Design and Control, Compliance and Impedance Control, Joint/Mechanism
Abstract: Highly rigid actuators such as geared motors or hydraulic actuators are widely used in industrial robots. To obtain high-speed motion, it is necessary to increase the actuator output as the robot weight increases. In contrast, humans perform motions using instantaneous force, such as jumping or throwing, via variable stiffness characteristics. We have developed a one-degree-of-freedom manipulator with a variable rheological joint using a straight-fiber-type artificial muscle and a magnetorheological (MR) brake. With the generation of instantaneous force, the dead and rise times decreased compared to the conventional method. After the generation of an arbitrary instantaneous force, we were able to control the robot’s arm position by applying an equilibrium force on the joint. Furthermore, we were able to control the vibrations of the arm by controlling the MR brake using an evaluation function.

Keywords: Variable Stiffness Actuator Design and Control, Smart Actuators, Medical Systems, Healthcare, and Assisted Living
Abstract: In a previous study we developed an expansion and contraction actuator using PVC gel. We investigated the characteristics of the PVC gel actuator and found that its stiffness changed noticeably with a variation in the applied DC field. In this study, we designed new variable stiffness spats for walking assistance by incorporating the variable stiffness PVC gel actuator in generally used spats. The stiffness of the spats can be varied with the on and off switching of an electric field. We believe that the spats can assist walking by restraining and releasing body motion with different stiffness while walking, and conducted experiments to evaluate their effectiveness. It was found that the integrated electromyogram (IEMG) and maximal voluntary contraction (%MVC) of the rectus femoris muscle decreased during walking when wearing them which indicated that the gel spats designed in this study were effective in assisting walking.

Attachments: Video Attachment
Keywords: Variable Stiffness Actuator Design and Control, Joint/Mechanism, Mechanism Design
Abstract: Robots with Variable Stiffness Actuators (VSA) are intrinsically flexible in the joints. The built-in mechanical spring not only has the advantage of a higher peak performance, but also leads to a more robust robot. This paper presents and analyzes the threats to a VSA equipped robot that arise from external or internal origin. Influences of mechanical, moisture, electrical, thermal, radiation, and chemical nature are identified. Protection methods from these threats are discussed and the results presented. The results are separated into hardware, observation, control limiters, and reaction strategies. A hierarchical implementation of the control limiters and reaction strategies is presented. The reaction strategies use a motor position deviation and a change in the stiffness setup to reduce the load at high passive deflections in the VSA. Control limiter and reaction strategies have been implemented in the DLR Hand Arm System and evaluated experimentally with impacts on the system.

Keywords: Variable Stiffness Actuator Design and Control, Force Control, Physical Human-Robot Interaction
Abstract: We present variable negative stiffness actuation (VnSA), an alternative method of achieving variable stiffness actuation based on the nonlinear deflection characteristics of buckling beams. The approach exploits transverse stiffness variations of axially loaded beams around their critical buckling load to achieve an actuator with adjustable stiffness. In particular, transverse stiffness of buckled beams are positive under tensile loading and for compressive loading below their first critical buckling load, while they display negative stiffness above this critical value. Furthermore, for small deflections transverse stiffness of buckled beams depends linearly on the amount of axial loading. Consequently, the stiffness of a variable stiffness actuator can be modulated (i) by decreasing the transverse stiffness through an increase of the axial compressive loading on a beam, up to values above the first critical buckling load where the overall stiffness of the actuator approaches its lowest negative value, and (ii) by increasing the transverse stiffness through application of tensile axial loading. Capitalizing on the concept of negative stiffness, the lowest stiffness of VnSA can be set arbitrarily close to zero or even to negative values (when counterbalanced), while very high stiffness values are also achievable by tensile loading of the beam. As a result, VnSA can modulate its stiffness over a uniquely large range that includes zero and negative stiffness values. Furthermore, thanks to the negative stiffness characteristics, the stiffness of VnSA can be kept very low without sacrificing the mechanical integrity and load bearing capacity of the actuator. We introduce the design of VnSA, theoretically analyze its stiffness modulation response, and provide implementation details of a prototype. We also provide experimental results detailing range of stiffness modulation and force tracking performance achieved with this prototype and discuss its correspondence with the theory.

Keywords: Variable Stiffness Actuator Design and Control, Mechanism Design, Biologically-Inspired Robots
Abstract: Nonlinear elasticity of transmission is indispensable in any passively variable stiffness mechanism. However, it remains obscure how to decide a desired nonlinear force-displacement function. On the other hand biological muscular actions are associated with stiffness/impedance variation in a wide range as demanded by everyday tasks. This paper addresses the issue of designing a nonlinear elastic transmission,where the elastic behaviour is obtained from the passive properties of biological muscle, which happens to be an exponential one, leading to existence of linearity between stiffness and force. In general, with passive damping, the transmission behaves as a mechanical impedance element, to be used in variable impedance actuation. Knowledge of the varying impedance is required to operate the transmission reliably. An off-line calibrated model can only be approximate and erroneous with noisy sensors and changing characteristics of the passive elements with time and environmental condition. This article implements an Extended Kalman Filter algorithm for on-line estimation of stiffness and impedance of such a damped series-elastic transmission. The underlined principle in stiffness-force affine relation is exploited favourably in stiffness estimation with reduced complexity. The effectiveness of the proposed estimator is examined through experiments on the mechanical transmission designed using the biological principle.

Keywords: Performance Evaluation and Benchmarking, Telerobotics, Industrial Robots
Abstract: Recently, offshore plants are demanded to secure natural resources more and more and it is strongly required unmanned ones for safety of human operators and less running costs. In this paper, a practical multi-user teleoperation system is proposed for monitoring, inspection, operation, and maintenance of the unmanned offshore plants. The proposed system is developed to control mobile manipulator in a cooperative way among multiple human operators for better performance. For this, two control schemes, hand-eye coordination and disjoint axes were introduced for easier intuitive control of the mobile manipulator and for better cooperative control among multi-user, respectively. A well-known passivity-based approach, the time-domain passivity approach was, in addition, adopted to maintain system stability. And then, the proposed multi-user teleoperation system was evaluated via a human-centered method with several quantitative metrics regarding task completion time and interaction forces. Experimental results showed that the proposed multi-user teleoperation system has the benefit in tasks requiring less task completion time and interaction forces.

Keywords: Telerobotics, Flexible Arms, Motion Control
Abstract: It is widely known that the problem of controlling a rigid bilateral teleoperator with time-delays has been effectively addressed since the late 80's. However, the control of flexible joint manipulators in a bilateral teleoperation scenario, with dynamic gravity compensation, remains an open problem. This work aims at filling this gap by presenting a new controller for bilateral teleoperators composed of a rigid local manipulator and a flexible-joint remote manipulator with dynamic gravity compensation and asymmetric variable time-delays in the communication channel. In order to dynamically compensate the gravity term, in the flexible joint manipulator, a change of coordinates which accounts for the joint and link gravity position drift is used. The rest of the controller is a simple PD scheme. Assuming that the human operator and the environment define passive maps from velocity to force, it is proved that velocities and local and remote position errors are bounded. Additionally, if the human operator and remote environment forces are zero then velocities asymptotically converge to zero and position tracking is established. Some simulations are presented in order to show the performance of the proposed controllers.

Keywords: Telerobotics, Networked Teleoperation, Motion Control
Abstract: This paper proposes a proportional plus damping injection (P + d) controller for bilateral teleoperators in the operational space. Unit quaternions are used to describe the end-effectors' orientation since they exhibit the well known property of being a singularity-free representation. The proposed controller does not need the measurement of the velocities, instead a passivity--based filter is used. Under the reasonable assumptions that the human operator and the environment define passive maps from force to velocity, it is proved that velocities and pose (position and orientation) errors between the local and the remote manipulators are bounded. Moreover, in the case that the human and the environment forces are zero, the velocities and pose errors converge asymptotically to zero. Finally, experimental validation using two robots of 6-Degrees-of-Freedom (DoF) shows the effectiveness of the proposed control scheme.

Keywords: Telerobotics, Dexterous Manipulation, Haptics and Haptic Interfaces
Abstract: This paper presents a bilateral telemanipulation framework where the master and slave sub-systems have different kinematic structures. A virtual object is defined on the master and slave sides and used to capture the human hand motion and to compute the related force feedback. The force feedback is determined imposing that the same wrench acts on the master and slave virtual objects. An abstraction from the sub-system structures is obtained focusing on the effects produced on the manipulated object. The proposed approach has been tested with an experimental setup consisting of two haptic interfaces able to capture index and thumb motions on the master side and a DLR-HIT Hand II as slave sub-system.