光学精密工程2023，Vol.31Issue(24)：3595-3605,11.DOI:10.37188/OPE.20233124.3595
基于改进灰狼算法的冗余机械臂轨迹跟踪与避障
Trajectory tracking and obstacle avoidance of a redundant robotic manipulator based on the improved grey wolf optimizer
摘要
Abstract
In this study,the trajectory tracking and obstacle avoidance of redundant robotic manipulators are unified as an optimization problem,and a trajectory-tracking optimizer with obstacle avoidance capabili-ty based on an improved grey wolf optimizer(IGWO)is proposed.First,the obstacle avoidance space is modeled using the bounding box method,and the GJK algorithm is used to calculate the minimum distance between the robotic manipulator and the obstacle.Second,a fitness function is derived,and a reward func-tion for obstacle avoidance is introduced to actively reward the optimizer such that the manipulator can track the target trajectory while avoiding obstacles.Third,the grey wolf optimizer(GWO)is improved using a random dispersion strategy to improve its global search ability and solve optimization problems more accurately.Finally,the effectiveness and superiority of the proposed method were verified using a nine-degree-of-freedom redundant robotic manipulator.The experimental results show that for a circu-lar target trajectory,the tracking error of the robotic manipulator is 0.21 mm.During the tracking pro-cess,the distance between the robotic manipulator and obstacle is not shorter than 70 mm.Compared to the GWO,the IGWO improved the tracking accuracy by 13%.The proposed trajectory tracking op-timizer can perform the trajectory tracking and obstacle avoidance tasks of redundant robotic manipula-tors with millimeter-level accuracy;the IGWO can effectively improve the convergence accuracy of the classical GWO.关键词
冗余机械臂/灰狼算法/轨迹跟踪/避障规划Key words
redundant robotic manipulator/grey wolf optimizer/trajectory tracking/obstacle avoidance分类
计算机与自动化引用本文复制引用
崔靖凯,周宇飞,贺顺锋,徐振邦,朱明超..基于改进灰狼算法的冗余机械臂轨迹跟踪与避障[J].光学精密工程,2023,31(24):3595-3605,11.基金项目
国家自然科学基金资助项目(No.62173047) （No.62173047）
