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作 者:武毅 胥超 刘力源 刘今越[1] 贾晓辉[1] 李铁军[1] WU Yi;XU Chao;LIU Liyuan;LIU Jinyue;JIA Xiaohui;LI Tiejun(School of Mechanical Engineering,Hebei University of Technology,Tianjin 300401)
出 处:《机械工程学报》2023年第15期83-93,共11页Journal of Mechanical Engineering
基 金:国家自然科学基金(U1813222,U20A20283)资助项目。
摘 要:针对基于梯度投影的冗余度机器人传统避障算法无法实现机器人在任务空间避障的问题,提出一种基于多任务转换的冗余度机器人控制算法。首先,基于传统算法中的Hm避障指标,提出投影矢量指标预筛选方法,利用障碍物在机器人连杆上的投影矢量筛选掉非避碰杆件,计算可能避碰杆件与障碍物的距离并通过距离比较得出最短距离,减少最短距离的运算量。其次,根据避障标志点与障碍物最短距离的变化,引入多任务转换因子,实现冗余度机器人在任务空间避障、关节空间避障、末端轨迹补偿任务之间的平稳转换。最后,采用平面三自由度机器人和七自由度冗余机器人分别进行对比仿真分析和试验验证。结果表明,机器人可以有效躲避不同位置下的障碍物,并实现运动过程中机器人关节角及关节角速度的平稳、连续变化。Aiming at the problem that the traditional obstacle avoidance algorithm of the redundant robot based on gradient projection cannot achieve obstacle avoidance in task space,a redundant robot control algorithm based on multi-task transformation is proposed.Firstly,based on the obstacle avoidance index Hm in the traditional algorithm,the projection vector index pre-screening method is proposed.The non-collision avoidance links are screened by the projection vector of the obstacle on the robot links.Then distances between possible collision avoidance links and the obstacle are calculated and the shortest distance is obtained by comparing the distances,which reduces the computation of the shortest distance.Secondly,according to the changes of the shortest distance between the obstacle avoidance mark points and the obstacle,the multi-task conversion factors are introduced to realize the smooth transformation of the redundant robot among task space obstacle avoidance,joint space obstacle avoidance,and end-effector trajectory compensation tasks.Finally,a planar 3-DOF redundant robot and a 7-DOF redundant robot are respectively used for comparative simulation analysis and experimental verification.The results show that the robot can effectively avoid obstacles in different positions,and the joint angles and joint angular velocities of the robot can change smoothly and continuously during the movement.
关 键 词:冗余度机器人 多任务转换 实时避障 投影矢量指标预筛选
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
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