Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

TL;DR

This paper presents a novel optimization algorithm combining Genetic Algorithm and Pattern Search to improve trajectory tracking accuracy for redundant manipulators, verified through simulations showing superior performance.

Contribution

It introduces a Generalized Pattern Search algorithm integrated with Genetic Algorithm for optimal trajectory planning in redundant manipulators.

Findings

GPS outperforms Genetic Algorithm in tracking accuracy

Simulations confirm improved trajectory tracking

Algorithm effective for different end-effector trajectories

Abstract

Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.