Decentralized Multi-AGV Task Allocation based on Multi-Agent Reinforcement Learning with Information Potential Field Rewards-Reference-Cited by-同舟云学术

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Decentralized Multi-AGV Task Allocation based on Multi-Agent Reinforcement Learning with Information Potential Field Rewards

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
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Author:

Li Mengyuan,Guo Bin,Zhang Jiangshan,Liu Jiaqi,Liu Sicong,Yu Zhiwen,Li Zhetao,Xiang Liyao

Funder

National Science Fund for Distinguished Young Scholars

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9637506/9637115/09637774.pdf?arnumber=9637774

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A review of recent advances, techniques, and control algorithms for automated guided vehicle systems;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2024-06-02

2. Interference-Aware Multihop Routing in UAV Networks: A Harmonic-Function-Based Potential Field Approach;IEEE Internet of Things Journal;2024-06-01

3. Real-Time Conflict-Free Path Planning for Multi-AGVs Based on Deep Reinforcement Learning;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

4. A scheduling optimization method for multiple automated guided vehicle systems;International Journal of Advanced Robotic Systems;2024-03-01

5. Cooperative Control of Multiple AGVs Based on Multi-Agent Reinforcement Learning;2023 IEEE International Conference on Unmanned Systems (ICUS);2023-10-13

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