速度约束下PSO的六自由度机械臂时间最优轨迹规划

摘要

The trajectory planning is designed for robot manipulators in the joint space according to interpolation points on the premise of the solutions to the forward and inverse kinematics problems of 6⁃DOF ( depth of field) ma⁃nipulators. This paper puts forward the particle swarm optimization ( PSO)⁃based time optimal trajectory planning of the 3⁃5⁃3 polynomial interpolation method in order to make mechanical arms run in the shortest time at a constrain⁃ed speed. The PSO is proposed to optimize run time due to its simple structure and easily adjustable parameters. The polynomial interpolation time rather than coefficient is selected as searching variable in PSO optimization. If the interpolation time of three polynomials doesn't meet the constraints, the particle will be excluded by comparison. The shortest time of the 6⁃DOF manipulators running at different speeds is obtained by offline PSO. Real⁃time ex⁃periments are conducted on the robot control platform. It shows that this method can accurately realize time optimal trajectory planning at any speed through its position, velocity and acceleration curves.%以六自由度机械臂的运动学正逆解为前提条件，在关节空间中根据插值点设计机器人的运动轨迹，为使机械臂在不同的速度约束下以最短时间运行，提出了粒子群优化速度约束下的时间最优3⁃5⁃3多项式插值轨迹规划方法。粒子群算法结构简单、实现容易，参数易调整，直接选择以多项式插值时间为变量的搜索空间中进行PSO优化，并且对不符合速度约束条件的插值时间进行筛选。通过离化得到六自由度机械臂限速运行下的最短时间，在机器人控制平台上进行实时实验，得到关节运动位置、速度、加速度曲线，证明了该方法能够准确地实现任意速度约束的时间最优轨迹规划。