Multi-objective optimization of a redundantly actuated parallel robot mechanism for special machining
Haiqiang Zhang, Jianglong Tang, Qing Gao, Guohua Cui, Kan Shi, Yan‐an Yao
Abstract
Abstract. In order to improve the accuracy and efficiency of special machining for a complex surface, a 2RPU-2SPR (where R, P, U, and S stand for revolute, prismatic, universal, and spherical joints, respectively) over-constrained redundantly actuated parallel robot mechanism is proposed. And six performance evaluation indexes are established to ensure the working performance including workspace, motion/force transmission efficiency, stiffness, dexterity, energy efficiency, and the inertia coupling index. Furthermore, a collaborative optimal configuration algorithm is conducted based on an orthogonal experimental design algorithm and a multi-objective particle swarm optimization algorithm. On the basis given above, a simulation analysis of a multi-objective optimization is conducted. Compared with two traditional, intelligent optimization algorithms of a multi-objective particle swarm optimization algorithm and an orthogonal experimental design method, the improved collaborative multi-objective optimization algorithm has a better optimization effect.