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Engineering the Evolution of Self-Organising Behaviours in Swarm Robotics: A Case Study

机译:工程研究群体机器人中自组织行为的演变:一个案例研究

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摘要

Evolutionary Robotics (ER) is a powerful approach for the automatic synthesis of robot controllers, as it requires little a priori knowledge about the problem to be solved in order to obtain good solutions. This is particularly true for collective and swarm robotics, in which the desired behaviour of the group is an indirect result of the control and communication rules followed by each individual. However, the experimenter must make several arbitrary choices in setting up the evolutionary process, in order to define the correct selective pressures that can lead to the desired results. In some cases, only a deep understanding of the obtained results can point to the critical aspects that constrain the system, which can be later modified in order to re-engineer the evolutionary process towards better solutions. In this paper, we discuss the problem of engineering the evolutionary machinery that can lead to the desired result in the swarm robotics context. We also present a case study about self-organising synchronisation in a swarm of robots, in which some arbitrarily chosen properties of the communication system hinder the scalability of the behaviour to large groups. We show that by modifying the communication system, artificial evolution can synthesise behaviours that properly scale with the group size.
机译:进化机器人技术(ER)是自动合成机器人控制器的强大方法,因为它不需要先验知识即可解决待解决的问题,从而获得良好的解决方案。对于集体机器人和群体机器人尤其如此,在这种情况下,组的期望行为是每个人遵循的控制和通信规则的间接结果。但是,实验人员必须在建立进化过程中做出几个任意选择,以便定义可以导致所需结果的正确选择压力。在某些情况下,只有对所获得结果的深刻理解才能指出约束系统的关键方面,以后可以对其进行修改,以便重新设计进化过程,以寻求更好的解决方案。在本文中,我们讨论了对进化机器进行工程设计的问题,这些问题可能会在群体机器人技术的背景下产生预期的结果。我们还提出了一个关于机器人群中自组织同步的案例研究,其中通信系统的某些任意选择的属性阻碍了行为向大型群体的扩展。我们表明,通过修改通信系统,人工进化可以合成与组规模适当缩放的行为。

著录项

  • 作者

    Trianni Vito; Nolfi Stefano;

  • 作者单位
  • 年度 2011
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  • 原文格式 PDF
  • 正文语种 en
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