Global path planning method for mobile logistics robot based on raster graph method

This paper proposes a global path planning method for mobile logistics robots based on the grid graph approach. The method constructs a warehouse environment easily understood by the robots using the grid graph technique. By dividing the global path planning problem into typical Traveling Salesman Problem (TSP) and Time-Sensitive TSP (TS-TSP) problems, the robots' initial position relative to the exit is considered. The paper presents a mathematical model for global path planning using population-based optimization algorithms such as Potential Field Ant Colony Optimization. The optimal visiting sequence for global path points is obtained using this method. Furthermore, an A* algorithm is used to compute the accurate global path planning results for the mobile logistics robots. Experimental results demonstrate that the proposed method achieves fast convergence, obtains the global optimal solution quickly, requires less computation time for global path planning, and exhibits strong practicality.

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Published on Bulletin of Science and Technology in December 2019.