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Models for the Design of Bioinspired Robot Eyes

机译:生物启发的机器人眼设计模型

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Active vision has the goal of improving visual perception; therefore, the investigation of ocular motion strategies must play an important role in the design of humanoid robot eyes. Listing''s law is a basic principle, which characterizes various ocular movements in humans, including saccades and smooth pursuit, and its neural or mechanical origin has been debated for a long time. Recent anatomical advances suggest that motions compatible with Listing''s law could be mainly caused by the mechanical structure of the eye plant. In this paper, we present a bioinspired model of the eye plant, and we formally prove that according to the model, the implementation of Listing''s law can be actually explained on the base of the geometry of the eye and of its actuation system. The proposed model is characterized by a limited number of geometric parameters, which can be easily used to set the guidelines for the design of humanoid, and possibly tendon-driven, robot eyes. Simulative and experimental tests performed on a robot prototype are eventually presented to perform a quantitative evaluation of the performance of the model, also in comparison with physiological data measured in humans and primates and reported in the literature.
机译:主动视觉的目的是改善视觉感知;因此,眼动策略的研究必须在类人机器人眼的设计中起重要作用。列表定律是基本原理,它表征了人类的各种眼动运动,包括扫视和平稳追赶,并且其神经或机械起源已经讨论了很长时间。最近的解剖学进展表明,与李斯特定律兼容的运动可能主要是由眼科植物的机械结构引起的。在本文中,我们提出了一种具有生物启发性的眼科植物模型,并正式证明了根据该模型,可以根据眼睛的几何形状及其驱动系统来实际解释清单定律的实现。 。所提出的模型的特点是几何参数数量有限,可以很容易地用于设置人形机器人(可能是腱驱动的机器人眼睛)设计准则。最终提出了对机器人原型进行的模拟和实验测试,以对模型的性能进行定量评估,还与人类和灵长类动物测量的生理数据进行了比较,并在文献中进行了报道。

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