Intelligent Logistics in Semiconductor Manufacturing: AGV Path Planning Driven by 3D Spatiotemporal A∗ Algorithm

In the semiconductor manufacturing industry, the path planning of Automated Guided Vehicles (AGVs) is directly related to production efficiency and logistics costs. However, the logistics systems inside semiconductor factories typically present a complex multi-level three-dimensional environment, constrained by factors such as dense equipment distribution, dynamic task generation, and path conflicts. To address this, this paper proposes an AGV path planning method based on a three-dimensional spatiotemporal A∗ algorithm. This method extends the traditional A∗ algorithm by incorporating the three-dimensional spatial characteristics and dynamic scheduling requirements of semiconductor manufacturing environments, introducing the time dimension into the path search process. By constructing a spatiotemporal state graph, it dynamically evaluates the reachability of each node in both the three-dimensional space and time dimensions, and implements efficient path optimization with conflict-avoidance strategies. Experimental results demonstrate that the proposed algorithm can effectively solve the path planning problem in semiconductor manufacturing environments, improving the overall operational efficiency of the logistics system. This research provides an efficient and practical path planning solution for intelligent logistics systems in complex manufacturing environments.