Design of Multi-AGV System with Tracking, Collision Avoidance and Coordination
Authors: 
Tongpo Zhang, Wuyan Zhao, Xu Zhu, Enggee Lim, Fei Ma, Limin YuAuthors Info & Claims
Tongpo Zhang, Wuyan Zhao, Xu Zhu, Enggee Lim, Fei Ma, Limin YuAuthors Info & ClaimsArticle No.: 3, Pages 1 - 7
Abstract
With the develop of industrial automation, a mature and adaptive tracking and collision avoidance in multi-AGV coordination system has a pressing demand. Most of the research focuses on a part of a multi-AGV coordination system such as tracking algorithms, collision avoidance methods and mechanism of coordination. In this paper, efforts have been made to design a AGV system covering a whole set of tracking, collision avoidance and formation functionalities with performance analysis. There are three major aspects for the construction, including collision avoidance, tracking, and coordination. Collision avoidance is integrated in the navigation algorithm, which is based on the map of surrounding environments built by Simultaneous Localization and Mapping (SLAM). It is expected to be smooth and automatic by timely adjusting velocity and distance between obstacles. Tracking of AprilTag is the second key function to complete the system. Every slave AGV is able to track the master AGV according to the visual information provided by the AprilTag, and maintain a specified distance to form a designated pattern. The coordination function is that the AGV system consist a cluster of vehicles in master or slave mode traversing an optimized path toward given destinations. The effectiveness of the system design is demonstrated through experiments. The paper provided the detailed design procedure, numerical analysis of the measurement data and recommendations for further improvement of the system design.
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Published In
December 2021
699 pages
ISBN:9781450385053
DOI:10.1145/3508546
Copyright © 2021 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 25 February 2022
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- Research-article
- Research
- Refereed limited
Funding Sources
- Jiangsu Data Science and Cognitive Computational Engineering Research Centre
- Research Enhancement Fund of XJTLU
- AI University Research Center(AI-URC)
- XJTLU Laboratory for Intelligent Computation and Financial Technology
- National Natural Science Foundation of China (NSFC)
Conference
ACAI'21
ACAI'21: 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence
December 22 - 24, 2021
Sanya, China
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