Interdepartmental Research Center E. Piaggio, University of Pisa, Via Diotisalvi, 2, 56126 Pisa, Italy.
Philos Trans R Soc Lond B Biol Sci. 2011 Nov 12;366(1581):3153-61. doi: 10.1098/rstb.2011.0152.
We report on recent work in modelling the process of grasping and active touch by natural and artificial hands. Starting from observations made in human hands about the correlation of degrees of freedom in patterns of more frequent use (postural synergies), we consider the implications of a geometrical model accounting for such data, which is applicable to the pre-grasping phase occurring when shaping the hand before actual contact with the grasped object. To extend applicability of the synergy model to study force distribution in the actual grasp, we introduce a modified model including the mechanical compliance of the hand's musculotendinous system. Numerical results obtained by this model indicate that the same principal synergies observed from pre-grasp postural data are also fundamental in achieving proper grasp force distribution. To illustrate the concept of synergies in the dual domain of haptic sensing, we provide a review of models of how the complexity and heterogeneity of sensory information from touch can be harnessed in simplified, tractable abstractions. These abstractions are amenable to fast processing to enable quick reflexes as well as elaboration of high-level percepts. Applications of the synergy model to the design and control of artificial hands and tactile sensors are illustrated.
我们报告了最近在模拟自然和人工手抓取和主动触觉过程方面的工作。从人类手部关于更频繁使用模式中自由度相关性的观察(姿势协同)出发,我们考虑了一个几何模型的含义,该模型可以解释这些数据,并且适用于在与被抓取物体实际接触之前塑造手时发生的预抓取阶段。为了将协同模型的适用性扩展到研究实际抓取中的力分布,我们引入了一个包括手部肌肉骨骼系统机械顺应性的改进模型。该模型的数值结果表明,从预抓取姿势数据中观察到的相同主要协同作用对于实现适当的抓取力分布也是基本的。为了说明触觉感知双域中协同的概念,我们回顾了如何利用触觉的复杂性和异质性的信息来简化、可处理的抽象化的模型。这些抽象化可以快速处理,以实现快速反应以及高级感知的细化。协同模型在人工手和触觉传感器的设计和控制中的应用也得到了说明。