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Research Article | Open Access

Two-level vehicle path planning model for multi-warehouse robots with conflict solution strategies and improved ACO

Pan Wu1, Lingshu Zhong2( ), Jingwen Xiong3, Yuhao Zeng3, Mingyang Pei3
College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
Department of Civil and Transportation Engineering, South China University of Technology, Guangzhou 510641, China
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Abstract

With the rapid development of warehouse robots in logistics and other industries, research on their path planning has become increasingly important. Based on the analysis of various conflicts that occur when the warehouse robot travels, this study proposes a two-level vehicle path planning model for multi-warehouse robots, which integrates static and dynamic planning to improve operational efficiency and reduce operating costs. In the static phase, the blockage factor is introduced to enhance the ant colony optimization (ACO) algorithm as a negative feedback mechanism to effectively avoid the blockage nodes during movement. In the dynamic stage, a dynamic priority mechanism is designed to adjust the routing strategy in real time and give the optimal path according to the real situation. To evaluate the model’s effectiveness, simulations were performed under different operating environments and application strategies based on an actual grid environment map. The simulation results confirm that the proposed model outperforms other methods in terms of average running distance, number of blocked nodes, percentage of replanned paths, and average running time, showing great potential in optimizing warehouse operations.

Keywords

path planningant colony optimizationwarehouse robottwo-level modelconflict strategy

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Journal of Intelligent and Connected Vehicles
Volume 6 Issue 2,
June 2023
Pages 102-112
DOI: 10.26599/JICV.2023.9210011
Cite this article:
Wu P, Zhong L, Xiong J, et al. Two-level vehicle path planning model for multi-warehouse robots with conflict solution strategies and improved ACO. Journal of Intelligent and Connected Vehicles, 2023, 6(2): 102-112. https://doi.org/10.26599/JICV.2023.9210011

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Received: 12 April 2023
Revised: 13 May 2023
Accepted: 29 May 2023
Published: 30 June 2023
© The author(s) 2023.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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