Sensing through body dynamics
Sensing through body dynamics
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DOI：
10.1016/j.robot.2006.03.005
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发表时间：
2006-08-31
影响因子：
4.3
通讯作者：
Pfeifer, R.
中科院分区：
文献类型：
--
作者：
Iida, F.;Pfeifer, R.
它已被证明，感觉形态和感觉运动协调增强机器人系统的感知能力。例如，分类和类别学习的任务可以通过利用形态约束、感觉-运动耦合以及与环境的交互来显著简化。本文认为，在感觉运动控制的背景下，它是必不可少的考虑身体动力学来自形态学特性和与环境的相互作用，以获得更多的洞察力的感觉运动协调的潜在机制，更一般的感知的性质。一个四足机器人的运动模型被用于仿真和真实的世界的案例研究。运动模型演示了如何吸引状态来自身体动力学影响的感官信息，然后可以用于识别稳定的行为模式和环境中的物理特性。对行为和感觉信息的全面分析导致对身体动力学可用于自主机器人系统的类别学习的潜在机制的更深入理解。(c)2006 Elsevier B. V.保留所有权利。
It has been shown that sensory morphology and sensory-motor coordination enhance the capabilities of sensing in robotic systems. The tasks of categorization and category learning, for example, can be significantly simplified by exploiting the morphological constraints, sensory-motor couplings and the interaction with the environment. This paper argues that, in the context of sensory-motor control, it is essential to consider body dynamics derived from morphological properties and the interaction with the environment in order to gain additional insight into the underlying mechanisms of sensory-motor coordination, and more generally the nature of perception. A locomotion model of a four-legged robot is used for the case studies in both simulation and real world. The locomotion model demonstrates how attractor states derived from body dynamics influence the sensory information, which can then be used for the recognition of stable behavioral patterns and of physical properties in the environment. A comprehensive analysis of behavior and sensory information leads to a deeper understanding of the underlying mechanisms by which body dynamics can be exploited for category learning of autonomous robotic systems. (c) 2006 Elsevier B.V. All rights reserved.