Path Planning for Power Inspection Robot Based on Improved PSO Algorithm and Dynamic Window Approach

This paper proposes a path planning method for power inspection robot based on improved Particle Swarm Optimization (PSO) and Dynamic Window Approach (DWA). First, we use an improved PSO (IPSO) to generate the globally optimal path. By introducing chaotic perturbations to initialize the initial state of particles, we can increase the convergence speed. Second, we extract the turning points from the planned global path as the target points, and the DWA algorithm is used to perform local path planning. Finally, the effectiveness of the proposed method is validated in Matlab. By combining IPSO with DWA for power inspection robot path planning, the PSO algorithm performs global searching in the search space, aiming to find better solution spaces. The DWA algorithm optimizes the robot’s trajectory within the given velocity space, considering the dynamic constraints and local environment information, leading to the generation of the robot’s optimal motion path. The results indicate that the approach proposed in the article demonstrates good performance in path planning.