基于量子粒子群算法的工业机器人时间最优轨迹规划

Time Optimal Trajectory Planning for Industrial Robot Based on QPSO Algorithm

轨迹规划作为机器人控制器的状态流输入,可以使机器人实现期望的作业任务。在轨迹规划中,运动执行受到各种物理约束条件的限制,并且有运动平滑性、效率等各方面要求。在进行机器人轨迹规划时,需要基于多项规划约束条件求出对应优化轨迹。针对这一问题,基于量子粒子群算法,对工业机器人进行时间最优轨迹规划。对运动学建模、轨迹规划原理及相关算法进行了介绍,并进行了仿真分析。仿真结果表明,基于量子粒子群算法进行工业机器人时间最优轨迹规划,可以保证机器人平稳高效地完成任务。

As the state flow input of the robot controller,trajectory planning can enable the robot to achieve the desired task.In trajectory planning,motion execution is limited by various physical constraints and required various aspects such as motion smoothness and efficiency.When planning robot trajectory,it is necessary to obtain corresponding optimized trajectory based on multiple planning constraints.To address this issue,quantum particle swarm optimization algorithm was used to perform time optimal trajectory planning for industrial robot.Kinematics modeling,trajectory planning principles and related algorithms were introduced,and simulation analysis was carried out.The simulation results show that using quantum particle swarm optimization algorithm for time optimal trajectory planning of industrial robot can ensure that the robot completes task smoothly and efficiently.