Conflict-free coordination planning for multiple automated guided vehicles in an intelligent warehousing system

With the rapid development of intelligent manufacturing, the application of automated guided vehicles (AGVs) in intelligent warehousing systems has become increasingly common. Efficiently planning the conflict-free paths of multiple AGVs while minimizing the total task completion time is crucial for evaluating the performance of the system. Distinguishing itself from recent approaches where conflict avoidance strategy and path planning algorithm are executed independently or separately, this paper proposes an improved conflict-free A* algorithm by integrating the conflict avoidance strategy into the initial path planning process. Based on the heuristic A* algorithm, we use the instruction time consumption as the key evaluation indicator of the cost function and add the turning consumption in the future path cost evaluation. Moreover, the expansion mode of child nodes is optimized where a five-element search set containing the “zero movement” is proposed to implement a proactive pause-wait strategy. Then the prediction rules are designed to add constraints to three types of instructions based on the timeline map, guiding the heuristic planning to search for conflict-free child nodes. Extensive simulations show that the coordination planning based on the improved conflict-free A* algorithm not only effectively achieves advanced conflict avoidance at the algorithmic level, but also exhibits lower computational complexity and higher task completion efficiency compared to other coordination planning methods.