In order to reduce the residual vibration of SCARA robot arm,particle swarm algorithm was selected as the optimization algorithm to find the optimal vibration suppression trajectory.The method of nonlinear decreasing inertia weight and particle population jumping was proposed to improve the particle swarm algorithm for the problem of poor convergence and stagnation in the trajectory finding of particle swarm algorithm.Using the robotic arm vibration suppression experimental platform,the improved particle swarm algorithm for vibration suppression trajectory optimization is experimentally studied to verify that the results are feasible and effective,and the optimal vibration suppression trajectory with the smallest vibration suppression index is obtained.