A SELF LEARNING MOTION PLANNING SYSTEM FOR MULTIPLE MOBILE ROBOTS BASED ON FUZZY-NEURO NETWORKS

In this paper,we discuss motion planning method for multiple mobile robots in a working environment. In order to move safely in the same workspace,robots must be able to track the velocity accurately deduced by its Planning System .Because of uncertainty of the accurate mathematical model and disturbance of the environment ,it is usually difficult to do so. In the worst case, crash between two robots may occur. A Self-adjusting Motion Planning System ,based on Fuzzy-Neuro networks, is proposed to adjust the actual velocity .Through off-line and on-line learning algorithm,a fuzzy logic controller is constructed to greatly minimize the tracking error, so the safety of the robots can be attained. Simulation results based on the scheme are presented to demonstrate its efficiency.