Cooperative control and communication of intelligent swarms: a survey
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Control Theory and Technology http://link.springer.com/journal/11768
Cooperative control and communication of intelligent swarms: a survey Kun HOU 1 , Yajun YANG 1† , Xuerong YANG 2 , Jiazhe LAI 1 1.Department of Aerospace Science and Technology, University of Aerospace Engineering, Beijing 101416, China; 2.School of Aeronautics and Astronautics, Sun Yat-Sen University, Guangzhou Guangdong 510275, China Received 12 December 2019; revised 18 March 2020; accepted 28 April 2020
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. Keywords: Intelligent swarm, cooperative control, communication, task assignment, bio-inspired methods, distributed sensor fusion, reinforcement learning DOI https://doi.org/10.1007/s11768-020-9195-1
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Introduction
Swarms [1–3] can be intelligent and powerful enough to solve complex problems. Many cases in natural world show us that limited swarms are often much mightier than individuals. For example, ants carry food several times heavier than their own weight together, termites
build nests cooperatively up to 9 meters high, bees can adjust the temperature of the hive, etc. In these cases, the communication between individuals promotes their cooperation. During the development of swarm intelligence, communication is the basic condition to improve swarm performance and achieve efficient cooperation.
† Corresponding author. E-mail: [email protected]. This work was supported by National Natural Science Foundation of China (No. 61803383).
© 2020 South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature
K. Hou et al. / Control Theory Tech, Vol.
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