Abstract: In order to improve the working efficiency and stability of the manipulator, a time-optimal quintic B-spline interpolation trajectory optimization algorithm based on improved particle swarm optimization (PSO) is proposed. The UR10 manipulator is taken as the research object. Firstly, the given trajectory points are interpolated by using the quintic B-spline curve. Secondly, aiming at the shortcomings of the traditional PSO algorithm, such as low solution accuracy and easy to fall into local optimum, the inertia weight and cognitive factor in the algorithm are adjusted to change the value dynamically with the increase of the number of iterations, so as to improve the global search ability in the early stage and the local search ability in the later stage. Finally, through three test functions and simulation experiments, the results show that the improved PSO algorithm can improve the accuracy of the solution and effectively improve the working efficiency of the manipulator.