Fuzzy Controller for Wall-Climbing Microrobots

Abstract

This paper presents a fuzzy control system that incorporates sensing, control and planning to improve the performance of the wall-climbing microrobots in unstructured environments. After introduction of the robot system, a task reference method is proposed which is based on a fuzzy multisensor data fusion scheme. The method provides a novel mechanism to efficiently integrate task scheduling, action planning and motion control in a unified framework. A robot gait generation method is described which switches the robot locomotion between different motion modes with the help of a finite state machine driven by sensory information. A fuzzy motion controller is designed to improve control performance and reduce power consumption by the suitable selection of fuzzy sets and inference methods, as well as the definition of corresponding membership functions and control rule bases. A fuzzy logic compensator is developed to compensate the gravitational effects according to different robot configurations and task situations. Experimental results prove the validity of the proposed methods.