基于DRMPSO的绳驱冗余机械臂逆运动学求解与运动规划

doi:10.16731/j.cnki.1671-3133.2025.09.007

现代制造工程 ›› 2025, Vol. 540 ›› Issue (9): 53-59.doi: 10.16731/j.cnki.1671-3133.2025.09.007

基于DRMPSO的绳驱冗余机械臂逆运动学求解与运动规划

刘洋¹, 李申^1,2, 刘飞², 宋小刚³

1 长江大学机械工程学院,荆州 434023;
2 深圳职业技术大学集成电路学院,深圳 518055;
3 哈尔滨工业大学(深圳)机电工程与自动化学院,深圳 518055

收稿日期:2024-09-04 出版日期:2025-09-18 发布日期:2025-09-23
通讯作者: 刘飞,博士,讲师,主要研究方向为绳驱机器人及其控制。E-mail:liufei8715@163.com。
作者简介:刘洋,博士,副教授,主要研究方向为智能算法和石油机械。E-mail:344632981@qq.com。
基金资助:
广东省教育厅科研项目(2023KTSCX317);深圳职业技术大学重点科研项目(6023310005K)

DRMPSO-based inverse kinematics solution and motion planning for cable-driven redundant manipulator

LIU Yang¹, LI Shen^1,2, LIU Fei², SONG Xiaogang³

1 School of Mechanical Engineering,Yangtze University,Jingzhou 434023,China;
2 School of Integrated Circuit,Shenzhen Polytechnic University,Shenzhen 518055,China;
3 School of Mechanical Engineering and Automation,Harbin Institute of Technology,Shenzhen 518055,China

Received:2024-09-04 Online:2025-09-18 Published:2025-09-23

摘要/Abstract

摘要： 为了解决绳驱冗余机械臂逆运动学求解问题,基于混沌映射和反向学习方法对粒子群算法进行改进,并引入子种群粒子和种群规模动态调整策略,提出一种混沌初始化的动态重组多种群粒子群优化算法(Dynamic Reorganization Multi-swarm Particle Swarm Optimization algorithm,DRMPSO)。建立绳驱冗余机械臂运动学模型,构造以机械臂末端最小位姿误差和最低能量消耗为目标的适应度函数。通过与其他算法对机械臂逆运动学求解问题进行比较,表明所提出的动态重组多种群粒子群优化算法在求解精度和稳定性上均具有明显的优势。最后,将动态重组多种群粒子群优化算法用于机械臂的运动规划中,仿真结果表明,动态重组多种群粒子群优化算法在使机械臂达到末端位置的同时还能保证姿态的连续性,机械臂运动过程流畅。

关键词: 绳驱冗余机械臂, 逆运动学, 粒子群优化算法, 混沌映射

Abstract: In order to solve the inverse kinematics solving problem of the cable-driven redundant manipulator,the particle swarm algorithm was improved based on the strategies of chaotic mapping and inverse learning,and sub-population particles as well as the dynamic adjustment strategy of the population size were introduced to propose a Dynamic Reorganization Multi-swarm Particle Swarm Optimization (DRMPSO) algorithm with chaotic initialization. The kinematic model of the cable-driven redundant manipulator was established,and the fitness function with the minimum position error and the minimum energy consumption at the end of the manipulator was constructed. By comparing with other algorithms for the inverse kinematics of the manipulator,the proposed dynamic reorganization multi-swarm particle swarm algorithm has obvious advantages in both solution accuracy and stability. Finally,the dynamic reorganization multi-swarm particle swarm algorithm was used in the motion planning of the robotic arm,and the simulation results show that the dynamic reorganization multi-swarm particle swarm algorithm can ensure the continuity of the attitude while the robotic arm reaches the end position,and the robotic arm motion process is smooth.

Key words: cable-driven redundant manipulator, inverse kinematics, particle swarm optimization algorithm, chaotic mapping

中图分类号:

TP242
TP18

刘洋, 李申, 刘飞, 宋小刚. 基于DRMPSO的绳驱冗余机械臂逆运动学求解与运动规划[J]. 现代制造工程, 2025, 540(9): 53-59.

LIU Yang, LI Shen, LIU Fei, SONG Xiaogang. DRMPSO-based inverse kinematics solution and motion planning for cable-driven redundant manipulator[J]. Modern Manufacturing Engineering, 2025, 540(9): 53-59.

参考文献

[1] PENG J,XU W,YANG T,et al.Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot[J].Nonlinear Dynamics,2020,101(1):233-253.
[2] LIU F,HUANG H,LI B,et al.A parallel learning particle swarm optimizer for inverse kinematics of robotic manipulator [J].Int J Intell Syst,2021,36:6101-6132.
[3] KUCUK S,BINGUL Z.Inverse kinematics solutions for industrial robot manipulators with offset wrists[J].Applied Mathematical Modelling,2014,38(7/8):1983-1999.
[4] BEKEY G A.Springer Handbook of Robotics (B.Siciliano and O.Khatib;2008)[Book Review][J].IEEE Robotics & Automation Magazine,2008,15(3):110.
[5] 房立金,高瑞.一般6R机器人逆运动学算法的改进[J].机械科学与技术,2018,37(9):1325-1330.
[6] EKREM Ö,AKSOY B.Trajectory planning for a 6-axis robotic arm with particle swarm optimization algorithm[J].Engineering Applications of Artificial Intelligence,2023,122:106099.
[7] KHAN H,KIM H H,ABBASI S J,et al.Real-time inverse kinematics using dual particle swarm optimization DPSO of 6-DOF robot for nuclear plant dismantling[J].IFAC-PapersOnLine,2020,53(2):9885-9890.
[8] GHOSH A,SINGH O,RAY A K.Inverse kinematic solution of a 7 DOF robotic manipulator using boundary restricted particle swarm optimization[J].IFAC-PapersOnLine,2022,55(1):101-105.
[9] ZHANG T,LIANG S,YONG C,et al.The Dynamic Factor Particle Swarm Optimization (DFPSO) to inverse kinematics of CMOR based on pose decomposition strategy[J].Fusion Engineering and Design,2023,197:114047.
[10] NING Y,LI T,DU W,et al.Inverse kinematics and planning/control co-design method of redundant manipulator for precision operation:Design and experiments[J].Robotics and Computer-Integrated Manufacturing,2023,80:102457.
[11] 王诚,候力.冗余机械臂逆运动学的多子群粒子群求解[J].机械设计与制造,2022(3):97-100.
[12] 杨康,熊瑞平,潘楚光,等.基于混合算法的七轴机器人逆解求解[J].组合机床与自动化加工技术,2022(2):29-32.
[13] 张铮,朱齐丹,吕晓龙,等.冗余机械臂运动学逆解的求解优化方法[J].吉林大学学报(工学版),2023,53(12):3379-3387.
[14] 刘崇辉,王桂荣,金英连,等.移动焊接机械臂自适应粒子群逆运动学求解算法[J].组合机床与自动化加工技术,2023(3):50-53,58.
[15] 陈卓凡,周坤,秦菲菲,等.基于改进量子粒子群优化算法的机器人逆运动学求解[J].中国机械工程,2024,35(2):293-304.
[16] CHEN C F,ZAIN A M,MO L P,et al.A new hybrid algorithm based on ABC and PSO for function optimization[C]//IOP Conference Series:Materials Science and Engineering.London :IOP Publishing,2020:012065.
[17] Al-BETAR M A,AWADALLAH M A,BRAIK M S,et al.Elk herd optimizer:a novel nature-inspired metaheuristic algorithm[J].Artificial Intelligence Review,2024,57(3):48.
[18] HAMAD R K,RASHID T A.GOOSE algorithm:a powerful optimization tool for real-world engineering challenges and beyond[J].Evolving Systems,2024,15(4):1249-1274.
[19] JIA H,RAO H,WEN C,et al.Crayfish optimization algorithm[J].Artificial Intelligence Review,2023,56(S2):1919-1979.

基于DRMPSO的绳驱冗余机械臂逆运动学求解与运动规划

DRMPSO-based inverse kinematics solution and motion planning for cable-driven redundant manipulator

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