Path Planning of Intelligent Robots Based on Improved A* Algorithm
A. S. Liu, Hongjie Liu · Journal of Physics Conference Series · 2025
Abstract With the swift advancement in science and technology, intelligent robots have increasingly drawn significant attention. Nonetheless, when employing the conventional A* algorithm for path planning, these robots encounter several challenges, including an excessive number of search nodes, prolonged computation times, and a high frequency of path inflection points. To enhance the path planning efficiency of intelligent robots, this paper introduces adaptive weights into the heuristic function of the A* algorithm and incorporates the concept of parent nodes. By doing so, the node search range in the A* algorithm is constrained, leading to a reduction in both the number of searched nodes and the required computation time. Furthermore, to address the issue of numerous path inflection points, this study applies the multiple uniform B-spline curve method to smooth the planned paths. This approach decreases the number of inflection points and ensures smoother transitions at sharp turns. Experimental results indicate that the improved A* algorithm proposed herein increases time efficiency by approximately 10%, reduces the scope of traversed nodes by around 50%, and effectively diminishes algorithmic runtime and path length while enhancing path.