Grid-Map-Based Path Planning and Task Assignment for Multi-Type AGVs in a Distribution Warehouse

Abstract

In an intelligent distribution warehouse, latent AGVs are used for horizontal handling, and forklift AGVs are used for horizontal or vertical handling. Studying the path planning and task assignment problem when the two types of AGVs are mixed can help improve the warehouse operation efficiency and reduce the warehouse operation cost. This paper proposes a two-stage optimization method to solve this problem. In the first stage, the warehouse plan layout is transformed into a raster map, and the shortest path between any two points of the warehouse without conflict with fixed obstacles is planned and stored using the A* algorithm combined with circular rules, and the planned shortest path is called directly in the subsequent stages. In the second stage, to minimize the task completion time and AGV energy consumption, a genetic algorithm combining penalty functions is used to assign horizontal handling tasks to submerged AGVs or forklift AGVs and vertical handling tasks to forklift AGVs. The experimental results show that the method can meet the 24 h operation requirements of an intelligent distribution warehouse and realize the path planning and task assignment of forklift AGVs and latent AGVs. And furthermore, the number of AGVs arranged in the warehouse can be further reduced.