Path planning of manipulator based on improved particle swarm optimization

Aiming at the shortcomings of traditional particle swarm optimization (PSO) in dealing with robotic arm path planning problems, such as premature and low convergence accuracy, an improved particle swarm optimization (IPSO) is proposed. While maintaining the advantage of first convergence of traditional PSO, the algorithm dynamically adjusts the particle speed according to the evolution trend of the population to balance the global and local search of particles. This paper takes PUMA560 manipulator as the research object, and uses the envelope method to transform the collision problem into the distance problem. Finally, the algorithm is compared with other algorithms in MATLAB. The simulation results show that the algorithm can effectively avoid falling into the minimum value, and the generated path is better, which helps the robotic arm to quickly find the optimal path.