Optimization design of a parallel surgical robot with remote center of motion

Abstract

This paper proposes a parallel surgical robot with a remote center of motion, and the kinematic optimization design is studied. The surgical robot is composed of two branches, each of which is a planar mechanism. The kinematics model of the robot is established through spatial geometric analysis. A modified Monte-Carlo sampling method is presented to greatly increase the sampling rate during the workspace calculation of the parallel surgical robot. Further, through the boundary sampling method, the boundary of the workspace is encrypted and sampled, and the accurate workspace is obtained. A dexterity index with clear physical meaning is proposed and the corresponding solution is found. Based on the effective workspace volume index and global dexterity index, a multi-objective optimization is carried out on the parallel surgical robot by using the quantum particle swarm optimization. The optimized robot has a large effective workspace and good dexterity, which meets the needs of surgical robots.