Unmanned Forklift Path Planning Method Based on Improved Hybrid A* Algorithm

Unmanned forklifts are an important part of the current intelligent logistics system, and their path planning problems directly affect the efficiency and safety of the logistics system. This paper improves the hybrid A* algorithm for the path planning problem of single-wheel steering unmanned forklift. First, the path planning problem of a single-wheel steering unmanned forklift was modeled and its kinematic constraints were analyzed. Then, the basic mechanism of the hybrid A* algorithm was analyzed, and the map environment evaluation index was proposed, and the motion step size of the hybrid A* algorithm was improved accordingly. This allows the algorithm to have different movement steps under different obstacle densities, which enhances the algorithm's adaptability to the environment. Finally, the feasibility of the path generated by the improved hybrid A* algorithm was verified through simulation experiments, and multiple sets of tests proved that the improved algorithm significantly reduced the expansion nodes and improved the algorithm performance.