Autonomous Navigation Path Planning Based on Improved A* Algorithm
Sheng Luo, Shiping Xu, Guoyang Cheng, Zhonghua Liu, Zhengbei Xin · 2025
In this paper, an improved A* path planning algorithm is proposed to optimize the performance of the traditional A* algorithm by introducing the pruning technique, the curvature and path length evaluation function, and the collision buffer mechanism. t improves the searching efficiency through the pruning technique; introduces the evaluation of curvature and path length to balance the smoothness and the lengths of paths, and generates paths that are more in line with the real mobility needs; and introduces the collision buffer mechanism, which prevents the paths close to obstacles, which effectively improves safety. The experimental results show that the improved algorithm significantly improves the search efficiency compared with the traditional method, the path planning time is reduced by about 44.14% on average, and the generated paths are smoother and in line with the requirements of real-life safe driving. The research results provide theoretical support and practical reference for autonomous navigation and obstacle avoidance of unmanned vehicles and intelligent driving. Future research can further optimize the reduction of the distance of the planned path to improve the obstacle avoidance effect and the overall performance of the system.