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

Miao Li; Hang Yin; Kenji Tahara; Aude Billard

doi:10.1109/ICRA.2014.6907861

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

Miao Li, Hang Yin, Kenji Tahara, Aude Billard

Control Systems

Research output: Contribution to journal › Conference article › peer-review

53 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 language	English
Article number	6907861
Pages (from-to)	6784-6791
Number of pages	8
Journal	Proceedings - IEEE International Conference on Robotics and Automation
DOIs	https://doi.org/10.1109/ICRA.2014.6907861
Publication status	Published - Sep 22 2014
Event	2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China Duration: May 31 2014 → Jun 7 2014

All Science Journal Classification (ASJC) codes

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

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10.1109/ICRA.2014.6907861

Cite this

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title = "Learning object-level impedance control for robust grasping and dexterous manipulation",

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.",

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AU - Li, Miao

AU - Yin, Hang

AU - Tahara, Kenji

AU - Billard, Aude

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N2 - 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.

AB - 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.

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JO - Proceedings - IEEE International Conference on Robotics and Automation

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

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All Science Journal Classification (ASJC) codes

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