Neural Network Reactive Navigation and Control of Wheeled Mobile Robot

  • Zenon Hendzel
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


A neural net real-time obstacle avoidance and control approach for mobile robot has been developed and numerically implemented. A collision-free path is calculated using an efficient neural net motion planer. The output of the navigation level is fed into a neural net tracking controller that takes into account the complete dynamics of the mobile robot. The proposed neural reactive navigation approach is based on the coordination of elementary behaviors. To avoid the convex obstacles the neural navigator fuses a ‘reaching the middle of a collision-free space’ behavior and a ‘goal-seeking’ behavior. A ‘wall-following’ behavior was conducted too, which can be applied to avoid the concave obstacles. The structure of the neural-net controller for nonholonomic mobile robot is derived using a filtered error approach. The effectiveness of the proposed method is numerically verified by a series of experiments on the emulator of wheeled mobile robot Pioneer-2DX.


Mobile Robot Trajectory Generation Navigation Task Adaptive Fuzzy Controller Wheel Mobile Robot 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Zenon Hendzel
    • 1
  1. 1.Department of Applied Mechanics and RoboticsRzeszow University of TechnologyRzeszowPoland

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