Learning object-level impedance control for robust grasping and dexterous manipulation

Miao Li, Hang Yin, Kenji Tahara, Aude Billard

Research output: Contribution to journalConference article

42 Citations (Scopus)

Abstract

Object-level impedance control is of great importance for object-centric tasks, such as robust grasping and dexterous manipulation. Despite the recent progress on this topic, how to specify the desired object impedance for a given task remains an open issue. In this paper, we decompose the object's impedance into two complementary components-The impedance for stable grasping and impedance for object manipulation. Then, we present a method to learn the desired object's manipulation impedance (stiffness) using data obtained from human demonstration. The approach is validated in two tasks, for robust grasping of a wine glass and for inserting a bulb, using the 16 degrees of freedom Allegro Hand mounted with the SynTouch tactile sensors.

Original languageEnglish
Article number6907861
Pages (from-to)6784-6791
Number of pages8
JournalProceedings - IEEE International Conference on Robotics and Automation
DOIs
Publication statusPublished - Sep 22 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: May 31 2014Jun 7 2014

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All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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