AGV Path Planning for Logistics Warehouse by Using an Improved D*Lite Algorithm

In order to solve the problem that the traditional automated guided vehicle (AGV) path planning algorithm has slow convergence speed and is easy to fall into local optimal solution, an improved D*lite algorithm is being presented by combining Dijkstra algorithm and D*lite algorithm. Firstly, the topological map is generated with grid graph. Then, AGV path planning is divided into two stages: pre-planning and real-time planning. In the pre-planning stage, the local shortest path can be achieved through forward searching with Dijkstra algorithm from start vertex to the goal vertex. In the real-time planning stage, the total shortest path can be computed through backward searching with improved D*lite algorithm which searches from the goal vertex to the start vertex and uses heuristics to focus the search, and uses similar ways to minimize having to reorder the priority queue. Finally, the simulation results indicate that the convergence speed and path distance of AGV are optimized by using the improved D*lite algorithm.