Abstract

In recent years, the research of multiple unmanned surface vessels collaboration has received great attention. More and more researchers have proposed different methods of multiple unmanned surface vessels collaboration, such as cooperative collision avoidance, formation, and rendezvous. Based on the significant advantages of biological swarm intelligence applications in these collaborative methods, this article summarizes the research methods of multiple unmanned surface vessels collaborative search and hunting from the perspective of swarm intelligence. First of all, this article summarizes the key technologies of multiple unmanned surface vessels collaborative search and hunting from the aspects of the multi-robot system, group communication, environment modeling, collaboration mechanism, and path planning. Then, it reviews some classic swarm intelligence algorithms, analyzes the advantages and disadvantages of these algorithms, and proposes optimization directions for existing disadvantages based on relevant literature. Finally, the article points out some existing problems in every stage and suggestions for future research.

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