Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Autoren

  • Yanan Li
  • Gowrishankar Ganesh
  • Nathanael Jarrasse
  • Sami Haddadin
  • Alin Albu-Schaeffer
  • Etienne Burdet

Organisationseinheiten

Externe Organisationen

  • Imperial College London
  • University of Sussex
  • National Institute of Advanced Industrial Science and Technology
  • Laboratoire de Robotique de Paris (LRP)
  • Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer8362715
Seiten (von - bis)1170-1182
Seitenumfang13
FachzeitschriftIEEE transactions on robotics
Jahrgang34
Ausgabenummer5
Frühes Online-Datum22 Mai 2018
PublikationsstatusVeröffentlicht - 5 Okt. 2018

Abstract

Humans can skilfully use tools and interact with the environment by adapting their movement trajectory, contact force, and impedance. Motivated by the human versatility, we develop here a robot controller that concurrently adapts feedforward force, impedance, and reference trajectory when interacting with an unknown environment. In particular, the robot's reference trajectory is adapted to limit the interaction force and maintain it at a desired level, while feedforward force and impedance adaptation compensates for the interaction with the environment. An analysis of the interaction dynamics using Lyapunov theory yields the conditions for convergence of the closed-loop interaction mediated by this controller. Simulations exhibit adaptive properties similar to human motor adaptation. The implementation of this controller for typical interaction tasks including drilling, cutting, and haptic exploration shows that this controller can outperform conventional controllers in contact tooling.

ASJC Scopus Sachgebiete

Zitieren

Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification. / Li, Yanan; Ganesh, Gowrishankar; Jarrasse, Nathanael et al.
in: IEEE transactions on robotics, Jahrgang 34, Nr. 5, 8362715, 05.10.2018, S. 1170-1182.

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Li, Y, Ganesh, G, Jarrasse, N, Haddadin, S, Albu-Schaeffer, A & Burdet, E 2018, 'Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification', IEEE transactions on robotics, Jg. 34, Nr. 5, 8362715, S. 1170-1182. https://doi.org/10.1109/TRO.2018.2830405
Li, Y., Ganesh, G., Jarrasse, N., Haddadin, S., Albu-Schaeffer, A., & Burdet, E. (2018). Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification. IEEE transactions on robotics, 34(5), 1170-1182. Artikel 8362715. https://doi.org/10.1109/TRO.2018.2830405
Li Y, Ganesh G, Jarrasse N, Haddadin S, Albu-Schaeffer A, Burdet E. Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification. IEEE transactions on robotics. 2018 Okt 5;34(5):1170-1182. 8362715. Epub 2018 Mai 22. doi: 10.1109/TRO.2018.2830405
Li, Yanan ; Ganesh, Gowrishankar ; Jarrasse, Nathanael et al. / Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification. in: IEEE transactions on robotics. 2018 ; Jahrgang 34, Nr. 5. S. 1170-1182.
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