基于改进粒子群算法的时间最优机械臂轨迹规划

Time-Optimal Trajectory Planning for Manipulator Based on Improved Particle Swarm Optimization Algorithm

针对机械臂关节空间轨迹规划的时间优化问题,结合机械臂运动约束,提出基于非线性动态改变惯性权重的粒子群优化(NPSO)算法.根据传统3-5-3多项式插值方法,采用改进粒子群算法寻求最短关节运动时间,研究线性递减改变惯性权重(LPSO)算法和NPSO算法的性能,选用NPSO算法完成关节运动时间最优求解.研究结果显示,经时间优化后的3-5-3插值曲线连续光滑且具备更好的运动特性,整体运动时间缩短约26%,证实提出的方法具有可行性.

Aiming at the time optimization problem of joint space trajectory planning of manipulator,a particle swarm optimization algorithm based on nonlinear dynamic change of inertia weight(NPSO)was proposed combined with the motion constraints of manipulator.According to the traditional 3-5-3 polynomial interpolation method,the improved particle swarm optimization algorithm was used to find the shortest joint motion time.The performance of particle swarm optimization algorithm based on linear decreasing inertia weight(LPSO)and NPSO algorithm were studied.NPSO algorithm was used to complete the optimal solution of joint motion time.The results show that the 3-5-3 interpolation curve after time optimization is continuous and smooth with better motion characteristics.The overall motion time was reduced by about 26%,which proved the feassibility of proposed method.