Fuzzy sensor-based motion control among dynamic obstacles for intelligent rigid-link electrically driven arm manipulators

An intelligent motion planning based on fuzzy rules for the idea of artific ial potential fields using analytic harmonic functions is presented. The pu rpose of the combination of a fuzzy controller and a robust controller is t o design a realistic controller for nonlinear electromechanical systems suc h as an electric motor actuating an arm robot. This control algorithm is ap plied to the three basic navigation problems of intelligent robot systems i n unstructured environments: autonomous planning, fast nonstop navigation w ithout collision with obstacles, and dealing with structured and/or unstruc tured uncertainties. To achieve this degree of independence, the robot syst em needs a variety of sensors to be able to interact with the real world. S onar range data is used to build a description of the robot's surroundings. The proposed approach is simple, computationally fast, and applies to whol e-arm collision avoidance. The stability of the overall closed loop system is guaranteed by the Lyapunov theory. Simulation results are provided to va lidate the theoretical concepts, and a comparative analysis demonstrates th e benefits of the proposed obstacle avoidance algorithm.