Research on Automatic Path Planning Method of Warehouse Inspection Robot

Abstract

The patrol robot is an important guarantee for the safety of the enterprise’s warehouse. However, due to the large number of patrol target points, the automatic path planning of the patrol robot is difficult and inefficient. In order to solve this problem, the hybrid particle swarm optimization (HPSO) algorithm is combined with A-star algorithm, and a path optimization method for inspection robot based on HPSO-A-star model is proposed. First, the grid model of the map is established, A-star algorithm calculates the path between two inspection points, and then HPSO algorithm realizes the nonlinear planning of the path according to the length of different paths, so as to find an optimal inspection route. The comparative experimental analysis results show that the path planned by HPSO algorithm is 5.71% shorter than that planned by PSO algorithm; the smaller the map grid size is, the shorter the calculated optimal path length is, but it will consume more computing resources. Finally, the HPSO-A-star algorithm is compared with the PSO-A-star algorithm; the experimental results show that the path of the HPSO-A-star algorithm is shortened by 29.79%, and the HPSO-A-star algorithm can better realize the path planning of the patrol robot.