Computer Engineering and Applications ›› 2022, Vol. 58 ›› Issue (6): 250-255.DOI: 10.3778/j.issn.1002-8331.2009-0455

• Engineering and Applications • Previous Articles     Next Articles

Time Optimal Trajectory Planning for Tandem Manipulator of Electric Energy Meter Test Platform

OU Xin, ZHOU Lu, ZHANG Zhi, WU Yuejia, ZHAO Yunbin   

  1. Guiyang Power Supply Bureau of Guizhou Power Grid Co., Ltd., Guiyang 550002, China
  • Online:2022-03-15 Published:2022-03-15



  1. 贵州电网有限责任公司 贵阳供电局,贵阳 550002

Abstract: Time optimal trajectory planning is helpful to shorten the movement time and improve the working efficiency of the manipulator, which plays a crucial role in the practical application scenarios of the manipulator. An optimal trajectory planning method based on an improved multi-population genetic algorithm is proposed to solve the point-to-point time-optimal trajectory planning problem of tandem robotic arms. The algorithm firstly fits the motion path of the robot arm through the fifth-degree polynomial interpolation and then optimizes the motion time of the robot arm by using the improved multi-population genetic algorithm. The improvements include:designing the fitness function with penalty term to reduce the probability of the individual being selected who does not meet the kinematic constraints. Greedy selection strategy is introduced to retain the excellent individuals in the parent population and replace the poor ones in the offspring population in proportion. The convergence speed of the algorithm is accelerated by adaptive adjustment of crossover and mutation probability. Finally, the feasibility of the proposed algorithm is verified by simulation experiments with ER-4iA robotic arm and compared with ant colony algorithm, particle swarm algorithm, standard genetic algorithm, and standard multi-population genetic algorithm, the results show that the proposed algorithm has better performance.

Key words: time optimal, trajectory planning, tandem manipulator, multi-population genetic algorithm

摘要: 时间最优轨迹规划有助于缩短机械臂运动时间,提高工作效率,在机械臂实际应用场景中起着至关重要的作用。针对串联机械臂点到点运动的时间最优轨迹规划问题,提出一种基于改进多种群遗传算法的最优轨迹规划方法。通过五次多项式插值对机械臂运动路径进行拟合,利用改进的多种群遗传算法对机械臂运动时间进行优化,改进之处包括:设计含有惩罚项的适应度函数,降低不满足运动学约束条件的个体被选择的概率;引入贪婪选择策略,按照比例保留父代种群优秀个体,替换子代种群较差个体;自适应调整交叉和变异概率,加快算法收敛速度。以ER-4iA机械臂为实验对象,通过仿真实验验证所提算法的可行性,并将所提算法与蚁群算法、粒子群算法、标准遗传算法和标准多种群遗传算法进行比较,结果表明所提算法具有更优的性能。

关键词: 时间最优, 轨迹规划, 串联机械臂, 多种群遗传算法