Trajectory tracking of redundant manipulators using an adaptive fuzzy algorithm

In this paper, the Adaptive Fuzzy Logic (AFL) algorithm proposed previously by us for solving inverse kinematics of redundant robots, has been improved for trajectory tracking applications. The main objective is to minimize the error of the end-effector at each point along the trajectory so that the end-effector can accurately track the prescribed trajectory. The rate of convergence to desired points has been improved considerably and therefore a simple accurate and fast trajectory tracking solution is obtained. The simulation results verify the efficiency of the proposed method.