TY - GEN
T1 - Design of multi-agv system with tracking, collision avoidance and coordination
AU - Zhang, Tongpo
AU - Zhao, Wuyan
AU - Zhu, Xu
AU - Lim, Enggee
AU - Ma, Fei
AU - Yu, Limin
N1 - Funding Information:
This research was funded by Research Enhancement Fund of XJTLU (REF-19-01-04), National Natural Science Foundation of China (NSFC) (Grant No. 61501380), and by AI University Research Center (AI-URC) and XJTLU Laboratory for Intelligent Computation and Financial Technology through XJTLU Key Programme Special Fund (KSF-P-02).
Publisher Copyright:
© 2021 ACM.
PY - 2021/12/22
Y1 - 2021/12/22
N2 - 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.
AB - 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.
KW - AGV coordination
KW - AGV tracking
KW - AprilTag
KW - Collision avoidance
KW - Path planning
UR - http://www.scopus.com/inward/record.url?scp=85125937573&partnerID=8YFLogxK
U2 - 10.1145/3508546.3508549
DO - 10.1145/3508546.3508549
M3 - Conference Proceeding
AN - SCOPUS:85125937573
T3 - ACM International Conference Proceeding Series
BT - Conference Proceeding - 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2021
PB - Association for Computing Machinery
T2 - 4th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2021
Y2 - 22 December 2021 through 24 December 2021
ER -