首页 /研究 /A Novel Mutating PSO Based Solution For Inverse Kinematic Analysis Of Multi Degree-Of-Freedom Robot Manipulators
SWARM

A Novel Mutating PSO Based Solution For Inverse Kinematic Analysis Of Multi Degree-Of-Freedom Robot Manipulators

Abubakar Umar, Zhanqun Shi, Wei Wang, Zulfiqar Ibrahim Bibi Farouk

发表年份
2019
引用次数
11

摘要

A novel mutating particle swarm based optimization (MuPSO) technique for solving inverse kinematic problems of robot manipulators was proposed. The parameters of the standard PSO (SPSO) were found to produce non-converging solutions, so the parameters were modified to accommodate the complex structure of robotic inverse kinematic problems. The new parameters were also made adaptive, changing non-linearly with time. A forced mutation function was introduced capable of pushing the algorithm out of stagnation (at local optima). A mathematical model for multi degree-of-freedom (DOF) robot inverse kinematics and the proposed MuPSO was developed, the mechanism and condition for mutation were also expressly defined. The new MuPSO algorithm was found to efficiently derive solutions for complex inverse Kinematic problems and satisfactorily break out of stagnation. It was compared with a previously proposed algorithm and was found to completely dominate that solution.

关键词

Inverse kinematicsKinematicsParticle swarm optimizationInverseRobot kinematicsControl theory (sociology)RobotMathematical optimizationMathematicsLocal optimum

相关论文

查看 SWARM 分类全部论文