An overview of 3D object grasp synthesis algorithms

  • Authors:

  • A. Sahbani;S. El-Khoury;P. Bidaud

  • Affiliations:

  • UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris, France and CNRS, UMR 7222, ISIR, F-75005, Paris, France;Learning Algorithms and Systems Laboratory, EPFL, CH-1015 Lausanne, Switzerland;UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris, France and CNRS, UMR 7222, ISIR, F-75005, Paris, France

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2012

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Abstract

This overview presents computational algorithms for generating 3D object grasps with autonomous multi-fingered robotic hands. Robotic grasping has been an active research subject for decades, and a great deal of effort has been spent on grasp synthesis algorithms. Existing papers focus on reviewing the mechanics of grasping and the finger-object contact interactions Bicchi and Kumar (2000) [12] or robot hand design and their control Al-Gallaf et al. (1993) [70]. Robot grasp synthesis algorithms have been reviewed in Shimoga (1996) [71], but since then an important progress has been made toward applying learning techniques to the grasping problem. This overview focuses on analytical as well as empirical grasp synthesis approaches.