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Tws-based path planning of multi-AGVs for logistics center auto-sorting

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Abstract

With the development of automation and intelligent technology, automatic guided vehicles (AGVs) are more and more widely used in Industrial and commercial scenarios. Especially in intelligent warehouses, the path planning of multi AGVs has become the focus of research. Effective path planning can improve the operational efficiency of the AGVs system, reduce energy consumption, and ensure operational safety. However, due to the influence of various factors, such as environment complexity, task conflict, load variation, etc., the multi-AGVs path planning becomes extremely complicated. This paper studied the multi-AGVs path planning problem for intelligent warehousing in logistics centers, so as to promote the automatic sorting of logistics centers. For a warehouse map of a given logistics center, the goal is to transport the maximum amount of goods between different sources and destinations within a specified time frame with the least amount of AGVs. The method includes transforming the warehouse map into a directed graph to frame the problem. This paper introduced two heuristic algorithms to schedule the AGVs path without collision. Experimental results demonstrate that the proposed methods outperform existing approaches, achieving higher sorting throughput within a given time while utilizing fewer vehicles.

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Acknowledgements

This work was supported by fund: the Doctoral Program of Innovation and Entrepreneurship in Jiangsu Province with NO.KFR20021, National Key Research and Development Program of China with NO.2022ZD0115403, and National Natural Science Foundation of China with NO.62072236.

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  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, No.29 Jiangjun Avenue, Nanjing, 211106, Jiangsu, China

    Liu Chunyan & Zhao Yunlong

  2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, No.29 Jiangjun Avenue, Nanjing, 211106, Jiangsu, China

    Li Bao

  3. College of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen University Town, Shenzhen, 518055, Guangdong, China

    Gu Chonglin

  4. College of Informatics, Xiamen University, No. 422, Siming South Road, Xiamen, 361005, Fujian, China

    Song Liang

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  1. Liu Chunyan
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Chunyan, L., Bao, L., Chonglin, G. et al. Tws-based path planning of multi-AGVs for logistics center auto-sorting. CCF Trans. Pervasive Comp. Interact. (2024). https://doi.org/10.1007/s42486-024-00151-2

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