Optimal manipulator parameter selection using evolutionary optimization technique

Abstract

This article discusses an approach to selecting the optimal design parameters of a manipulator for minimum performance variations. The variations in desired performance of the manipulator are attributed to the effect of uncertainty in design, process and noise factors. To incorporate the effect of uncertainties in design parameters, a modification in evolutionary optimization approach is proposed. A worst-case approach has been used to model the uncertainties and simulate the performance of the manipulator while performing a task. The design parameters obtained from this optimization process are insensitive to the effect of uncertainties. The proposed approach has been illustrated with the help of a 2-DOF RR planar manipulator. This approach has also been implemented in a genetic algorithm to compare the computational advantage of the proposed modification in the differential evolution technique. The optimal design parameters are observed to be different for different tasks and trajectories in the workspace.