Mobility Path Planning for Underwater Autonomous Robots Using an Improved A* Algorithm

This paper examines the path planning problem for underwater autonomous robots using an improved A algorithm. As underwater robots are increasingly employed in marine exploration and resource development, path planning has emerged as a key technology. While the traditional A algorithm can effectively solve path planning problems, it has limitations in complex underwater environments, such as producing overly long paths and having low computational efficiency. To address these issues, this paper introduces an improved A* algorithm that enhances adaptability and search efficiency in underwater settings through a dynamic weight adjustment mechanism and heuristic function optimization. Simulation results demonstrate that this improved algorithm significantly outperforms the traditional A* algorithm in both path length and computation time, offering a more efficient path planning solution for underwater autonomous robots.