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• [P766] An Embedded Interval Type-2 Neuro-Fuzzy Controller for Intelligent Navigation of Mobile Robot
  Author(s): Siti Nurmaini
  
  

  Abstract
  This paper describes motion control using an embedded interval type-2 fuzzy - neuro controller. Weightless neural network strategy is used because fast learning, easy hardware implementation and well suited to microcontroller-based-real-time systems. The weightless neural network utilizes previous sensor data and analyzes the situation of the current environment and classifies geometric feature such as U-shape, corridor and left or right corner. The behavior of mobile robot is implemented by means of interval type-2 fuzzy control rules can be generated directly from the neuro classifier. This functionality is demonstrated on a mobile robot using modular platform and containing several microcontrollers implies the implementation of a robust architecture. The proposed architecture implemented using low cost range sensor and low cost microprocessor. The experiment results show that the mobile robot can recognize the current environment and was able to successfully avoid obstacle in real time and using proposed controller achieved smother motion compare on-off and fuzzy type-1.

  
   

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