The path planning of automated guided vehicles (AGV) is an important research topic in the field of industrial production and logistics. Collision-free path planning of multiple AGVs is a difficult problem in research. In this paper

based on the actual industrial production site

the traditional A* algorithm is improved by using the Chebyshev distance

which significantly reduces the search time and the number of search nodes of the A* algorithm

and improves the path search efficiency at the same time. The improved A* algorithm combined with the time window algorithm is used to solve this problem. Pre-judge the node occupancy on multiple AGV paths through the time window model

and dynamically adjust the AGV priority according to the production task requirements and the distance of the AGV from the end point. This algorithm effectively solves the deadlock and collision problems caused by multiple AGVs driving at the same time. The experimental results show that when the algorithm is used for dynamic path planning of multiple AGVs

the path search efficiency is significantly improved and the path conflict problem is effectively resolved.