Optimal design of manipulator parameter using evolutionary optimization techniques

Abstract

A robot must have high positioning accuracy and repeatability for precise applications. However, variations in performance are observed due to the effect of uncertainty in design and process parameters. So far, there has been no attempt to optimize the design parameters of manipulator by which performance variations will be minimum. A modification in differential evolution optimization technique is proposed to incorporate the effect of noises in the optimization process and obtain the optimal design of manipulator, which is insensitive to noises. This approach has been illustrated by selecting optimal parameter of 2-DOF RR planar manipulator and 4-DOF SCARA manipulator. The performance of proposed approach has been compared with genetic algorithm with similar modifications. It is observed that the optimal results are obtained with lesser computations in case of differential evolution technique. This approach is a viable alternative for costly prototype testing, where only kinematic and dynamic models of manipulator are dealt with.