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Application of Automated Guided Vehicles in Smart Automated Warehouse Systems: A Survey

Zheng Zhang, Juan Chen*, Qing Guo
Beijing University of Chemical Technology, Beijing, 100029, China
* Corresponding Author: Juan Chen. Email: jchen@mail.buct.edu.cn
(This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2022.021451

Received 15 January 2022; Accepted 10 May 2022; Published online 21 June 2022


Automated Guided Vehicles (AGVs) have been introduced into various applications, such as automated warehouse systems, flexible manufacturing systems, and container terminal systems. However, few publications have outlined problems in need of attention in AGV applications comprehensively. In this paper, several key issues and essential models are presented. First, the advantages and disadvantages of centralized and decentralized AGVs systems were compared; second, warehouse layout and operation optimization were introduced, including some omitted areas, such as AGVs fleet size and electrical energy management; third, AGVs scheduling algorithms in chessboardlike environments were analyzed; fourth, the classical route-planning algorithms for single AGV and multiple AGVs were presented, and some Artificial Intelligence (AI)-based decision-making algorithms were reviewed. Furthermore, a novel idea for accelerating route planning by combining Reinforcement Learning (RL) and Dijkstra’s algorithm was presented, and a novel idea of the multi-AGV route-planning method of combining dynamic programming and Monte-Carlo tree search was proposed to reduce the energy cost of systems.


Automated guided vehicles (AGVs); smart automated warehouse systems; AGVs scheduling; AGVs route planning; artificial intelligence (AI)
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