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Cooperative control and communication of intelligent swarms: a survey

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Abstract

Individuals exchange information, experience and strategy based on communication. Communication is the basis for individuals to form swarms and the bridge of swarms to realize cooperative control. In this paper, the multi-robot swarm and its cooperative control and communication methods are reviewed, and we summarize these methods from the task, control, and perception levels. Based on the research, the cooperative control and communication methods of intelligent swarms are divided into the following four categories: task assignment based methods (divided into market-based methods and alliance based methods), bio-inspired methods (divided into biochemical information inspired methods, vision based methods and self-organization based methods), distributed sensor fusion and reinforcement learning based methods, and we briefly define each method and introduce its basic ideas. Based on WOS database, we divide the development of each method into several stages according to the time distribution of the literature, and outline the main research content of each stage. Finally, we discuss the communication problems of intelligent swarms and the key issues, challenges and future work of each method.

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Authors and Affiliations

  1. Department of Aerospace Science and Technology, University of Aerospace Engineering, Beijing, 101416, China

    Kun Hou, Yajun Yang & Jiazhe Lai

  2. School of Aeronautics and Astronautics, Sun Yat-Sen University, Guangzhou Guangdong, 510275, China

    Xuerong Yang

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  1. Kun Hou
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  2. Yajun Yang
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Corresponding author

Correspondence to Yajun Yang.

Additional information

This work was supported by National Natural Science Foundation of China (No. 61803383).

Kun HOU received the B.E. degree in Aerospace Engineering from Tsinghua University, Beijing, China, in 2018. He is currently pursuing the M.E. degree in Aerospace Science and Technology with the Aerospace Engineering University, Beijing, China. His current research interests include distributed swarm intelligence and the cooperative navigation and active control of mulit-UAVs.

Yajun YANG received the Ph.D. degree from National University of Defense Technology, Hunan, China, in 2016. He has held teaching appointments at the Aerospace Engineering University since 2016. His current research interests include aircraft dynamics and control and the cooperative navigation and active control of UAV swarms. He has published more than 20 papers, 11 patents and 1 monograph.

Xuerong YANG is an associate professor and doctoral supervisor at Sun Yat-sen University, Guangzhou, China. His current research interests include space system control and simulation, space system parallel test, intelligent control and application of areospace swarms. He has published more than 40 academic papers in the field of aerospace technology, edited and translated 5 monographs, applied for more than 20 national invention patents, and applied for 6 software Copyrights. He has also served as a committee member of the Automation Institute System Simulation committee, the Parallel Control committee, the Command and Control Institute Space Safety Parallel System committee, and the Simulation Application committee of the simulation institute.

Jiazhe LAI received the Ph.D. degree from National University of Defense Technology Institute of Electronics, Chinese Academy of Sciences, Beijing, China. He is an associate researcher at the Aerospace Engineering University. His current research interests include system simulation. He has published more than 20 papers, 6 patents and 2 monograph.

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Hou, K., Yang, Y., Yang, X. et al. Cooperative control and communication of intelligent swarms: a survey. Control Theory Technol. 18, 114–134 (2020). https://doi.org/10.1007/s11768-020-9195-1

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