Willibald, Christoph und Eiband, Thomas und Lee, Dongheui (2020) Collaborative Programming of Conditional Robot Tasks. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020-10-25 - 2020-10-29, Las Vegas, NV, USA (Virtual). doi: 10.1109/iros45743.2020.9341212. ISBN 978-172816212-6. ISSN 2153-0858.
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Kurzfassung
Conventional robot programming methods are not suited for non-experts to intuitively teach robots new tasks. For this reason, the potential of collaborative robots for production cannot yet be fully exploited. In this work, we propose an active learning framework, in which the robot and the user collaborate to incrementally program a complex task. Starting with a basic model, the robot's task knowledge can be extended over time if new situations require additional skills. An on-line anomaly detection algorithm therefore automatically identifies new situations during task execution by monitoring the deviation between measured- and commanded sensor values. The robot then triggers a teaching phase, in which the user decides to either refine an existing skill or demonstrate a new skill. The different skills of a task are encoded in separate probabilistic models and structured in a high-level graph, guaranteeing robust execution and successful transition between skills. In the experiments, our approach is compared to two state-of-the-art Programming by Demonstration frameworks on a real system. Increased intuitiveness and task performance of the method can be shown, allowing shop-floor workers to program industrial tasks with our framework.
elib-URL des Eintrags: | https://elib.dlr.de/139209/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
Titel: | Collaborative Programming of Conditional Robot Tasks | ||||||||||||||||
Autoren: |
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Datum: | 2020 | ||||||||||||||||
Erschienen in: | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||
DOI: | 10.1109/iros45743.2020.9341212 | ||||||||||||||||
ISSN: | 2153-0858 | ||||||||||||||||
ISBN: | 978-172816212-6 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | Learning from Demonstration; Programming by Demonstration; Human-Robot Collaboration; Intuitive Programming; Interactive Robot Learning | ||||||||||||||||
Veranstaltungstitel: | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | ||||||||||||||||
Veranstaltungsort: | Las Vegas, NV, USA (Virtual) | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 25 Oktober 2020 | ||||||||||||||||
Veranstaltungsende: | 29 Oktober 2020 | ||||||||||||||||
Veranstalter : | IEEE | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||
HGF - Programmthema: | Technik für Raumfahrtsysteme | ||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||
DLR - Forschungsgebiet: | R SY - Technik für Raumfahrtsysteme | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Intuitive Mensch-Roboter Schnittstelle [SY] | ||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) | ||||||||||||||||
Hinterlegt von: | Willibald, Christoph | ||||||||||||||||
Hinterlegt am: | 07 Dez 2020 11:11 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:40 |
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