Path Planning for Mobile Robots Based on Improved A* Algorithm

Addressing the issues of excessive redundant nodes, non-smooth paths, and low search efficiency in the path planning process of the traditional A* algorithm, this paper proposes an improved Dynamic Expansion Neighborhood A* algorithm for optimal path planning. Firstly, building upon the traditional A* algorithm, the search neighborhood is dynamically expanded by combining the 8-neighbor and 24-neighbor search algorithms, dynamically adjusting the search scope to reduce redundant nodes. Secondly, through modification of the heuristic function, introducing weights, and optimizing the estimation function to enhance path search efficiency. Finally, the obtained path is subjected to smoothing processing to eliminate corner sharp points, improving path smoothness. Simulation results demonstrate that the improved A* algorithm outperforms the traditional algorithm in terms of length, node count, and smoothness of the planned path.