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On the Influence of Sensor Morphology on Vergence

机译:论传感器形态对易变的影响

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In the field of developmental robotics, a lot of attention has been devoted to algorithms that allow agents to build up skills through sensorimotor interaction. Such interaction is largely affected by the agent's morphology, that is, its shape, limb articulation, as well as the position and density of sensors on its body surface. Despite its importance, the impact of morphology on behavior has not been systematically addressed. In this paper, we take inspiration from the human vision system, and demonstrate using a binocular active vision platform why sensor morphology in combination with other properties of the body, are essential conditions to achieve coordinated visual behavior (here, vergence). Specifically, to evaluate the effect of sensor morphology on behavior, we present an information-theoretic analysis quantifying the statistical regularities induced through sensorimotor interaction. Our results show that only for an adequate sensor morphology, vergence increases the amount of information structure in the sensorimotor loop.
机译:在发展机器人技术领域,很多的关注一直致力于算法,让代理商通过感觉的互动建立技能。这种相互作用在很大程度上是由代理人的形态,即,它的形状,四肢关节,以及在它的身体表面的传感器的位置和密度的影响。尽管它的重要性,形态对行为的影响尚未得到系统解决。在本文中,我们从人类视觉系统的灵感,并证明了用双目主动视觉平台,为什么在与身体的其他属性组合传感器的形态,是实现协调的视觉行为(在这里,辐辏)的必要条件。具体而言,以评估对行为传感器形态的影响,提出了一种信息理论分析定量通过感觉相互作用引起的统计规律。我们的结果表明,只有一个适当的传感器的形态,聚散度增加在感觉循环信息结构的量。

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