基于改进粒子群算法的六自由度机械臂轨迹优化

Trajectory Optimization of 6-DOF Manipulator Based on Improved Particle Swarm Algorithm

提出了一种基于改进粒子群算法的六自由度机械臂轨迹优化方法。以机械臂运行时间为目标函数,采用3-5-3多项式插值拟合轨迹,利用改进粒子群优化算法结合动态调整学习因子和自适应惯性权重,快速、准确地找到最优解,改善了基本粒子群算法容易陷入局部最优的问题。在机械臂工作空间内选择可到达的路径点,获取路径点处的关节角度,利用该算法获得平滑、连续且机械臂运行时间最优的机械臂运动轨迹曲线。仿真结果表明,基于改进粒子群算法的机械臂轨迹优化方法能够实现机械臂运行时间最优轨迹规划,具有较高的优化性能和实用性,可为六自由度机械臂运动轨迹规划提供有力支持。

A trajectory optimization method of six-degree-of-freedom manipulator based on improved particle swarm algorithm is proposed.Taking the running time of the manipulator as the objective function,the trajectory is fitted by 3-5-3 polynomial interpolation,and the optimal solution is found quickly and accurately by using the improved particle swarm optimization algorithm combined with dynamic adjustment of learning factors and adaptive inertia weight,which improves the problem that the basic particle swarm algorithm is easy to fall into local optimization.The reachable path points are selected in the workspace of the manipulator,and the joint angles at the path points are obtained.The smooth,continuous and optimal trajectory curve of the manipulator is obtained by using this algorithm.The simulation results show that the trajectory optimization method of manipulator based on improved particle swarm algorithm can realize the optimal trajectory planning of manipulator running time,and has high optimization performance and practicability,which can provide strong support for the trajectory planning of six-degree-of-freedom manipulator.