Intelligent Look-ahead Controllers for Nonholonomic Mobile Robot Manipulator

Abstract

This paper presents a planning and control algorithm for nonholonomic mobile robots (NMRs). The proposed controller uses the Look-ahead method that is based on feedback linearization technique; the linearization is achieved between the control inputs and the appropriate outputs. Hence the system can be decoupled. The controlled system consists of manipulator mounted on a mobile platform. The end-point of the manipulator is guided. It is desirable that the mobile platform is able to move as to position the manipulator in certain preferred configurations. Since the motion of the manipulator is unknown a priori, the platform has to use the manipulator position for motion planning. The simulations were carried with four techniques, self-tuning fuzzy PD (STFPD) controller, self-tuning neuro-fuzzy PD (STNFPD) controller, optimized PD (OPD), and PID (OPID) controllers with genetic algorithm (GA). The simulations comparison is carried out with the MATLAB/Simulink. Simulation results are presented to illustrate the efficacy of the proposed algorithm.