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• [P675] Environment Recognition System based on Multiple Classification Analyses for Mobile Robots
  Author(s): Atsushi Kanda, Masanori Sato, Kazuo Ishii
  
  

  Abstract
  Ruts formed as a result of vehicle traversal on soft ground are used by expert off road drivers because they can improve vehicle safety on turns and slopes thanks to the extra lateral force they provide to the vehicle. In this paper we propose a rut detection and tracking algorithm for Autonomous Ground Vehicles (AGVs) equipped with a laser range finder. The proposed algorithm utilizes an Extended Kalman Filter (EKF) to recursively estimate the parameters of the rut and the relative position and orientation of the vehicle with respect to the ruts. Simulation results show that the approach is promising for future implementation.

  
   

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