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Identification of Common Force-based Robot Skills from the Human and Robot Perspective

Eiband, Thomas und Lee, Dongheui (2021) Identification of Common Force-based Robot Skills from the Human and Robot Perspective. In: 20th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2020. IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids), 2021-07-19 - 2021-07-21, Munich, Germany. doi: 10.1109/HUMANOIDS47582.2021.9555681. ISBN 978-172819372-4. ISSN 2164-0572.

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Offizielle URL: https://ieeexplore.ieee.org/document/9555681

Kurzfassung

Learning from Demonstration (LfD) can significantly speed up the knowledge transfer from human to robot, which has been proven for relatively unconstrained actions such as pick and place. However, transferring contact or force-based skills (contact skills) to a robot is noticeably harder since force and position constraints need to be considered simultaneously. We propose a set of contact skills, which differ in the force and kinematic constraints. In a first user study, several subjects were asked to term a variety of force-based interactions, from which skill names were derived. In a second and third user study, the identified skill names are used to let a test group of subjects classify the shown interactions. To evaluate the skill recognition from the robot perspective, we propose a feature-based classification scheme to recognize such skills with a robotic system in a LfD setting. Our findings prove that humans are able to understand the meaning of the different skills and, using the classification pipeline, the robot is able to recognize the different skills from human demonstrations.

elib-URL des Eintrags:https://elib.dlr.de/143584/
Dokumentart:Konferenzbeitrag (Vorlesung)
Zusätzliche Informationen:Factory of the Future
Titel:Identification of Common Force-based Robot Skills from the Human and Robot Perspective
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Eiband, ThomasThomas.Eiband (at) dlr.dehttps://orcid.org/0000-0002-1074-9504NICHT SPEZIFIZIERT
Lee, DongheuiDongheui.Lee (at) dlr.dehttps://orcid.org/0000-0003-1897-7664NICHT SPEZIFIZIERT
Datum:Juli 2021
Erschienen in:20th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2020
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.1109/HUMANOIDS47582.2021.9555681
ISSN:2164-0572
ISBN:978-172819372-4
Status:veröffentlicht
Stichwörter:Robots; contact-based skills; force-based skills; context understanding; skill learning; learning from demonstration; lfd; programming by demonstration; pbd; decision support system; intuitive programming; interactive teaching; interactive classification
Veranstaltungstitel:IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)
Veranstaltungsort:Munich, Germany
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:19 Juli 2021
Veranstaltungsende:21 Juli 2021
Veranstalter :IEEE-RAS
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Robotik
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R RO - Robotik
DLR - Teilgebiet (Projekt, Vorhaben):R - Autonome, lernende Roboter [RO], R - Erklärbare Robotische KI, R - Intuitive Mensch-Roboter Schnittstelle [RO]
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Robotik und Mechatronik (ab 2013)
Hinterlegt von: Eiband, Thomas
Hinterlegt am:26 Nov 2021 10:49
Letzte Änderung:24 Apr 2024 20:43

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