Abstract: A^* algorithm is widely used in path planning for indoor inspection robots because of its better accuracy characteristics, but A^* algorithm exists problems such as low efficiency, many path points, and high path cost in path planning, and A^* algorithm has more inflection points in path searching process in complex environments, so A^* algorithm usually needs to be improved to improve algorithm usage performance in practical applications. Based on the jump-point search method, we propose the limited jump-point search method (Limited-JPS) using optimized pruning rules, and combined with the angular cost function, local path replacement, removal of path redundancy points and path smoothing, we propose an improved A^* algorithm based on Limited-JPS. To verify the feasibility and effectiveness of the improved A^* algorithm based on Limited-JPS, experimental validation is performed. The experimental results show that the improved A^* algorithm performs well in improving the path planning efficiency, reducing the path cost and improving the path smoothing under the premise of guaranteeing the effectiveness of the jump point search method as much as possible, and its performance is better than that of the standard A^* algorithm, thus proving that the improved A^* algorithm is effective.

Key words: indoor inspection robot, A^* algorithm, path planning, jump point search