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

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 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

Fingerprint

All Science Journal Classification (ASJC) codes

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

Cite this

Li, M., Yin, H., Tahara, K., & Billard, A. (2014). Learning object-level impedance control for robust grasping and dexterous manipulation. Proceedings - IEEE International Conference on Robotics and Automation, 6784-6791. [6907861]. https://doi.org/10.1109/ICRA.2014.6907861

@article{2a6fc535b7a34f90b2a710c5ac98fa9b,

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.",

author = "Miao Li and Hang Yin and Kenji Tahara and Aude Billard",

year = "2014",

month = "9",

day = "22",

doi = "10.1109/ICRA.2014.6907861",

language = "English",

pages = "6784--6791",

journal = "Proceedings - IEEE International Conference on Robotics and Automation",

issn = "1050-4729",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Learning object-level impedance control for robust grasping and dexterous manipulation

AU - Li, Miao

AU - Yin, Hang

AU - Tahara, Kenji

AU - Billard, Aude

PY - 2014/9/22

Y1 - 2014/9/22

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.

UR - http://www.scopus.com/inward/record.url?scp=84929208215&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84929208215&partnerID=8YFLogxK

U2 - 10.1109/ICRA.2014.6907861

DO - 10.1109/ICRA.2014.6907861

M3 - Conference article

AN - SCOPUS:84929208215

SP - 6784

EP - 6791

JO - Proceedings - IEEE International Conference on Robotics and Automation

JF - Proceedings - IEEE International Conference on Robotics and Automation

SN - 1050-4729

M1 - 6907861

ER -

Access to Document

10.1109/ICRA.2014.6907861