Abstract: In order to meet the demand for efficient and smooth operation of the robotic arm in complex assembly scenarios, a 4-5-4 polynomial interpolation trajectory planning method combined with an improved particle swarm optimization (PSO) algorithm is proposed under the time-impact optimality constraint. Firstly, based on the standard Denavit-Hartenberg (D-H) method, a simulation model of the robotic arm is established, and the kinematic solution and verification are carried out. Secondly, for the traditional particle swarm algorithm, which is prone to fall into the problem of local optimality, it is improved through the initialization of population chaos, the introduction of the simulated annealing algorithm Metropolis criterion, optimization of the dynamic factor, and the optimal polynomial interpolating curves at the end of the robotic arm are solved to validate the algorithm’s. Finally, the influence of the time shock factor on the optimization effect is explored, when the time factor β₁=0.6, shock factor β₂=0.4, the optimization effect is the best, and compared with the pre-optimization, the working efficiency of the robotic arm is improved by 27.5%, and the shock value is reduced by 26.36%.