IoT 21(24): e5

Research Article

Improvised multi-robot cooperation strategy for hunting a dynamic target

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  • @ARTICLE{10.4108/eai.8-2-2021.168691,
        author={Oussama Hamed and Mohamed Hamlich},
        title={Improvised multi-robot cooperation strategy for hunting a dynamic target},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={6},
        number={24},
        publisher={EAI},
        journal_a={IOT},
        year={2021},
        month={2},
        keywords={Multi-Robot System (MRS), hunting, path planning, multiagent cooperation},
        doi={10.4108/eai.8-2-2021.168691}
    }
    
  • Oussama Hamed
    Mohamed Hamlich
    Year: 2021
    Improvised multi-robot cooperation strategy for hunting a dynamic target
    IOT
    EAI
    DOI: 10.4108/eai.8-2-2021.168691
Oussama Hamed1,*, Mohamed Hamlich1
  • 1: ISSIEE Laboratory ENSAM, University of Hassan II, Morocco
*Contact email: oussamahamed11@gmail.com

Abstract

Hunting moving targets with random motions and behavior is a challenge for robotic systems, and it occupies a significant position in the research on coordination and cooperation in multi-robot systems. Cooperative hunting between robots is used in a wide range of fields such as industry, military, rescue and other fields. The aim of this paper is to present a new strategy for target hunting by means of a cooperative multi-robot system in two-dimensional space, especially moving targets with random and unexpected behavior. The strategy is inspired from the behavior of wolves in hunting and Wolf Swarm Algorithm, as it summarizes the roles of robots in the system in three roles: the leader wolf, the antagonist wolf, and the follower wolf. This diversity of roles contributed to improve the convergence performance of the algorithm and reduce significantly the pursuit time. The validity of this strategy is supported by computer simulations.