Abstract: Aiming at the problems of long trajectory time-consuming and poor stability in the trajectory planning process of the robotic arm, a robotic arm trajectory optimisation method with the objective of time-optimisation and using the quantum tunneling perturbation strategy particle swarm optimization (QTP-PSO) algorithm is proposed. Firstly, a mathematical model is established to improve the three kinds of weight coefficients of the traditional particle swarm algorithm, which are automatically adjusted according to the search process and the fitness function to improve the search efficiency of the algorithm. Secondly, a quantum tunnelling perturbation strategy is introduced in the particle position updating process to help the particles jump out of the suboptimal solution. Thirdly, the trajectory of the robotic arm is interpolated by 3-5-3 polynomials, and the trajectory is optimised using the improved algorithm under the velocity constraints. Finally, Matlab is used to simulate and conduct real welding experiments using the robotic arm. The experimental results show that compared with the traditional PSO algorithm, the convergence speed and fitness of QTP-PSO algorithm are significantly improved. After optimizing the trajectory interpolation time by using QTP-PSO algorithm, the overall motion time is 1.528 s, which is about 49.1% shorter than before optimization. The welding speed, quality and aesthetics are improved compared with those before optimisation. The improved algorithm effectively improves the working efficiency and stability of the robotic arm on the basis of ensuring the constraints.