基于改进粒子群算法的机械臂轨迹规划研究

Research on Manipulator Trajectory Planning Based on Improved Particle Swarm Optimization Algorithm

为提高机械臂的适用性和工作效率,针对机械臂关节空间时间最优轨迹规划问题,在研究传统的多项式插值轨迹规划方法基础上,结合改进的粒子群优化算法,通过动态调整学习因子,结合线性惯性权重,改善传统粒子群算法容易陷入局部最优的缺点,快速准确得到最优解;在机械臂工作空间中选取可到达的路径点,获取路径点处的关节角度,采用3-5-3分段插值多项式法规划机械臂的运动轨迹,同时利用改进粒子群算法优化轨迹的运行时间,得到平滑、连续且时间最优的运动轨迹曲线。Matlab仿真实验结果验证了该方法进行轨迹规划的可行性和有效性。

In order to improve the applicability and efficiency of the manipulator, in view of the manipulator joint space time optimal trajectory planning problems, a traditional trajectory planning method based on polynomial interpolation is studied.Combined with the improved particle swarm optimization algorithm, through the study of dynamic adjustment factor, combined with the linear inertia weight, the traditional particle swarm optimization algorithm is improved, which is easy to fall into local optimum shortcomings, and the optimal solution can be obtained quickly.The accessible waypoints are selected in the workspace of the manipulator, and the joint angles at the waypoints are obtained, the 3-5-3 piecewise interpolation polynomial method is used to plan the trajectory of the manipulator, and the improved particle swarm optimization algorithm is used to optimize the running time of the trajectory, and the smooth, continuous and time-optimal trajectory curve is finally obtained.Matlab simulation results verify the feasibility and effectiveness of this method for trajectory planning.