广西科技大学学报2026，Vol.37Issue(3)：1-11,11.DOI:10.16375/j.cnki.cn45-1395/t.2026.03.001
基于IMOPSO的IRB6700机器人轨迹优化
Trajectory optimization of IRB6700 robots based on IMOPSO algorithm
摘要
Abstract
To address the shortcomings of robotic systems,including low operational efficiency,high energy consumption,and excessive impact,as well as the limitations of the traditional multi-objective particle swarm optimization(MOPSO)algorithm such as slow convergence and susceptibility to local optima,a multi-objective particle swarm algorithm incorporating linear differential decreasing inertia weights and Gaussian variational operator was proposed to optimize the time-energy-impact multiobjective trajectory.First,taking the IRB6700 industrial robot as the research object,an improved D-H parameter method was used to establish the robot linkage coordinate system.And the forward and inverse kinematic equations of the robot were derived.The simulation model was then established with the help of MATLAB Robotics Toolbox to verify the correctness of the forward and inverse kinematics.Subsequently,the displacement,velocity and acceleration at different path nodes were trajectory planned by the 7-times B-spline interpolation.Finally,the improved multi-objective particle swarm optimization(IMOPSO)algorithm was used to optimize the planned trajectories by the 7-times B-spline interpolation method under the kinematic constraints.The results show that the running time of the robot was reduced from 25 seconds to 17 seconds while the acceleration and impact about time graphs became smoother.In addition,the robot starting point velocity and acceleration were both zero,thereby reducing energy consumption and joint impact.These findings prove that the IMOPSO algorithm in the paper can effectively realize the time-energy-impact multi-objective optimal trajectory planning.关键词
工业机器人/运动学分析/轨迹规划/多目标优化/IMOPSOKey words
industrial robot/kinematic analysis/trajectory planning/multi-objective optimization/IMOPSO algorithm分类
信息技术与安全科学引用本文复制引用
韩玉凤,尹辉俊,陈佳艺..基于IMOPSO的IRB6700机器人轨迹优化[J].广西科技大学学报,2026,37(3):1-11,11.基金项目
广西科技计划重点研发项目(桂科AB21220052) （桂科AB21220052）
广西科技计划项目(桂科攻1348005-12) （桂科攻1348005-12）
广西自然科学基金项目(2013GXNSFAA019319)资助 （2013GXNSFAA019319）
