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

In order to improve the motion performance and work efficiency of the grasping system, this paper takes the interpolation time of the manipulator trajectory as the target to optimise, and realizes the optimization analysis of the manipulator 3-5-3 mixed polynomial trajectory by improving the intelligent optimization algorithm. Targeting the defect that the standard particle swarm optimisation algorithm easily gets stuck in the local optimum when searching iteratively, the inertia weight function and learning factor in the algorithm are improved. Through simulation experiments, the trajectory running time and motion parameters optimized by the four algorithms are compared, and the improved particle swarm optimisation algorithm has the best optimization effect on the interpolation time of the manipulator 3-5-3 mixed polynomial trajectory.