Frontiers in Neurorobotics (Aug 2017)

Postural Hand Synergies during Environmental Constraint Exploitation

  • Cosimo Della Santina,
  • Matteo Bianchi,
  • Giuseppe Averta,
  • Giuseppe Averta,
  • Simone Ciotti,
  • Simone Ciotti,
  • Visar Arapi,
  • Simone Fani,
  • Simone Fani,
  • Edoardo Battaglia,
  • Manuel Giuseppe Catalano,
  • Manuel Giuseppe Catalano,
  • Marco Santello,
  • Antonio Bicchi,
  • Antonio Bicchi

DOI
https://doi.org/10.3389/fnbot.2017.00041
Journal volume & issue
Vol. 11

Abstract

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Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.

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