摘要
本文将冗余机械臂的轨迹跟踪和避障规划统一为优化问题,提出了一种基于改进灰狼算法的避障跟踪优化器。首先,基于包围盒法对避障空间进行了建模,使用GJK算法计算机械臂与障碍物之间的最小距离。其次,设计了适应度函数,引入避障奖励项对优化器进行主动奖励,使机械臂在跟踪目标轨迹的同时避开障碍物。然后,使用随机分散策略对灰狼算法进行了改进,以增强算法的全局搜索能力,从而更好地求解优化问题。最后,使用九自由度冗余机械臂验证了所提出方法的有效性和优越性。实验结果表明:对于圆形目标轨迹,机械臂的末端跟踪误差为0.21 mm;跟踪过程中,机械臂与障碍物的距离不小于70 mm;相比于经典灰狼算法,改进灰狼算法使跟踪精度提高了13%。本文提出的避障跟踪优化器能以毫米级的精度同时满足冗余机械臂的轨迹跟踪和避障任务;改进的灰狼算法能有效提高经典灰狼算法的收敛精度。
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.
作者
崔靖凯
周宇飞
贺顺锋
徐振邦
朱明超
CUI Jingkai;ZHOU Yufei;HE Shunfeng;XU Zhenbang;ZHU Mingchao(Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2023年第24期3595-3605,共11页
Optics and Precision Engineering
基金
国家自然科学基金资助项目(No.62173047)。
关键词
冗余机械臂
灰狼算法
轨迹跟踪
避障规划
redundant robotic manipulator
grey wolf optimizer
trajectory tracking
obstacle avoidance
