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Evolving autonomous specialization in congested path formation task of robotic swarms

机译:不断发展的自主专业化在机器人群的拥挤路径形成任务中

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Redundancy in the number of robots is a fundamental feature of robotic swarms to confer robustness, flexibility, and scalability. However, robots tend to interfere with each other in a case, where multiple robots gather in a spatially limited environment. The aim of this paper is to understand how a robotic swarm develops an effective strategy to manage congestion. The controllers of the robots are obtained by an evolutionary robotics approach. The strategy of managing congestion is observed in the process of generating a collective path of robots visiting two landmarks alternately. The robotic swarm exhibits autonomous specialization that the robots traveling inside the path activate the LEDs, while the robots in the outer side deactivate them. We found that the congestion is regulated in an emergent way of autonomous specialization by the result of an artificial evolution.
机译:机器人数量的冗余是机器人群体的基本特征,可赋予其健壮性,灵活性和可扩展性。然而,在多个机器人聚集在空间受限的环境中的情况下,机器人趋于彼此干扰。本文的目的是了解机器人群如何制定有效的策略来管理拥塞。机器人的控制器是通过进化机器人方法获得的。在生成机器人交替访问两个地标的集体路径的过程中,观察到了管理拥塞的策略。机器人群表现出自治专长,即在路径内行驶的机器人会激活LED,而外侧的机器人会禁用它们。我们发现,拥塞是通过人工进化的结果以自主专业化的新兴方式进行调节的。

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