Volume 3 · Issue 1 (2026)
Path Planning Optimization for Warehouse Robots Using Enhanced A* Search Algorithm
Ye Shao
School of Computer and Communication Engineering, Pujiang Institute, Nanjing Tech University, Nanjing 211200, China
Corresponding Author: Ye Shao (shaoye71@163.com)
Abstract: To address the problems of low efficiency and poor adaptability in path planning for current intelligent warehouse systems, this paper proposes an improved A* algorithm for path planning of intelligent vehicles in indoor warehouse environments. By optimizing the heuristic function, introducing a dynamic weight mechanism, and implementing path smoothing, the algorithm improves computational efficiency and path quality while maintaining path optimality. Experimental results show that the improved algorithm reduces planning time by approximately 25% and decreases path turning points by 40% compared to the traditional A* algorithm. The proposed approach effectively handles scenarios with both static and dynamic obstacles in warehouse environments. This research provides a practical solution for path planning in intelligent warehouse systems and demonstrates significant engineering application value.
Keywords: Agricultural green and low-carbon transition; Common prosperity; Practical paths; Northern foot of Qinling Mountains
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