基于多目标粒子群优化算法的6R工业机器人轨迹优化  

Trajectory Optimization for 6R Industrial Robot based on Multi-object PSO

作　　者：李丽[1,2] 房立金[3] 王国勋 Li Li;Fang Lijin;Wang Guoxun(School of Mechanical Engineering ＆ Automation,Northeastern University,Shenyang 110189,China;Faculty of Robot Science and Engineering,Northeastern University,Shenyang 110189,China;School of Mechanical Engineering,Shenyang Ligong University,Shenyang 110159,China)

机构地区：[1]东北大学机械工程与自动化学院,辽宁沈阳110189 [2]沈阳理工大学机械工程学院,辽宁沈阳110159 [3]东北大学机器人科学与工程学院,辽宁沈阳110189

出　　处：《机械传动》2018年第8期17-22,90,共7页Journal of Mechanical Transmission

基　　金：国家自然科学基金(51575092)

摘　　要：为了提高工业机器人的工作效率以及运动稳定性,对机器人轨迹进行了优化。在机器人任务空间中用NURBS曲线描述机器人末端轨迹,采用机器人逆运动学求解算法将任务空间轨迹转化到关节空间;提出了一种自适应罚函数的约束多目标骨干粒子群优化算法,对机器人运动时间、加速度、跃度等指标进行多目标优化,该算法采用自适应指数罚函数对约束进行处理,有利于引导算法更快进入可行区域,搜索好的目标值。最后,通过机器人加工实验,验证所提出算法的正确性和有效性。In order to improve the working efficiency and stability of industrial robots,the trajectory of the robot is optimized. In the robot task space,the NURBS curve is used to describe end effector trajectory,the algorithm of the inverse kinematics of the robot is used to transform the task space trajectory into the joint space.A constrained backbones multi-objective particle swarm optimization algorithm with adaptive penalty function is proposed to optimize the time,velocity,acceleration and jerk of the industrial robot. The algorithm uses the adaptive exponential penalty function to deal with the constraints,which help to guide the algorithm to enter the feasible area faster,and search better target value. Finally,the correctness and validity of the proposed algorithm are verified by robot machining experiment.

关 键 词：机器人 轨迹优化 粒子群 多目标优化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP242.2[自动化与计算机技术—控制科学与工程]