冗余机械臂逆运动学的多子群粒子群求解  

Redundant Manipulators Inverse Kinematics Problem Solution Method by Multiple Sub-Groups Particle Swarm Algorithm

作　　者：王诚 候力 WANG Cheng;HOU Li(Shanghai Civil Aviation College,Shanghai 200232,China;Sichuan University,Sichuan Chengdu 610065,China)

机构地区：[1]上海民航职业技术学院,上海200232 [2]四川大学,四川成都610065

出　　处：《机械设计与制造》2022年第3期97-100,共4页Machinery Design & Manufacture

基　　金：上海高校青年教师培养资助计划项目(JTZ10008)。

摘　　要：为了提高冗余机械臂逆运动学求解精度,提出了多子群粒子群算法的求解方法。使用D-H法建立了冗余机械臂运动学模型,以机械臂末端执行器位姿误差最小为目标构造了目标函数。在粒子群算法基础上,提出了粒子的多策略进化方法和多子群协同搜索方法,粒子的不同子群对应不同的进化方法,也即具有不同的搜索优势,从而提高算法应对不同类型寻优问题的能力。经运动学逆解仿真分析,多子群粒子群算法和粒子群算法搜索的最优粒子对应姿态误差相差5个数量级,位置误差相差4个数量级,充分证明了多子群粒子群算法的寻优性能远远优于粒子群算法;经多工作点实验验证,多子群粒子群算法的稳定性和鲁棒性也优于粒子群算法。In order to improve solving accuracy of redundant manipulator inverse kinematics problem,multiple sub-groupsPSO is proposed to solve it. Redundant manipulators dynamic model is built by D-H method,and object function is constructed by setting the goal of maximum position error and attitude error. On the basis of PSO,multi-strategy evolution method and multiple sub-groups co-searching method are put forward. Different sub-group possesses different evolution method,that means it possesses different searching advantage,so that the optimizing ability of algorithm to different style problem is improved. By inverse kinematics simulation analysis,attitude error corresponding to optimal particle differ 5 orders of magnitude of multiple sub-groups PSO and PSO,and position error differ 4 orders of magnitude,which proves that optimizing property of multiple sub-groups PSO is far better than PSO. Clarified by multiple working points inverse kinematics solution,stability and robust of multiple subgroups PSO is also better than PSO.

关 键 词：冗余机械臂 逆运动学 多子群粒子群算法 多策略进化 

分 类 号：TH16[机械工程—机械制造及自动化] TH11