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Improvised multi-robot cooperation strategy for hunting a dynamic target

机译:提高了狩猎动态目标的多机器人合作策略

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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, 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.
机译:狩猎随机动作和行为的移动目标是机器人系统的挑战,它占据了多机器人系统的协调与合作研究中的重要地位。 机器人之间的合作狩猎用于各种领域,如行业,军事,救援和其他领域。 本文的目的是通过在二维空间中的协同多机器人系统,特别是随机和意外行为的移动目标来展示一个新的目标狩猎策略。 该战略的灵感来自狼群在狩猎中的行为,因为它总结了机器人在系统中的三个角色中的作用:领导者狼,敌人的狼和追随者狼。 这种多样性的角色有助于提高算法的收敛性能,并显着降低追求时间。 计算机仿真支持此策略的有效性。

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