Considering the time optimization for robotic manipulator trajectory planning, the motion trajectory of 6R serial robotic manipulator is analyzed and studied. According to the robot kinematic characteristics, a time-optimal method based on the improved particle swarm algorithm is proposed with adopting the polynomial curve trajectory combined with the particle swarm optimization notion. The kinematic model of the robotic manipulator is constructed by the method of screw theory, and the joint trajectory is constructed by using the quintic polynomial curve in the joint space, and the optimal time sequence is solved by the improved PSO algorithm with minimizing running time as the objective function to complete the optimization of the trajectory. In the algorithm parameter setting, adaptive inertia weight factor and dynamic learning factor strategy are used to improve the standard particle swarm algorithm, which improves the search speed and global convergence ability of the algorithm. The effectiveness of the planning method based on the improved PSO optimization algorithm and the quintic polynomial function is verified by the optimization results using the handling condition as a simulation example. The results show that the method can ensure that the angular displacement, angular velocity and angular acceleration curves of each joint of the robotic manipulator are continuously smooth without sudden changes, and reduce the running time from 7.2 s to 6.64 s, with an overall runtime improvement of about 8.43% over the before optimization, which effectively improves the efficiency and smoothness of the robotic manipulator operation.