Path Tracking and Avoiding Obstacles of Mobile Robot in Dynamic Environment

Abstract

The problems of mobile robot on-line path tracking and real-time avoiding obstacles in a dynamic environment are studied.A method of fuzzy neural networks(FNN)combined with fuzzy logic control(FLC)is presented.A scheme of mobile robot on-line path tracking is designed based on FNN according as kinematics models of mobile robot and the interval relation between point and line.A reformative BP algorithm is used to complete the network learning and training.The gradient descending method is utilized to adjust the weight and threshold value of this network,which makes the error mean square deviation between reality output and expected output be minimum.The FLC is utilized to fulfill the real-time avoiding obstacles.Simulation results show that the method is efficient and possesses better abilities of dynamic path tracking and real-time avoiding obstacles with regard to an unknown dynamic environment.