Pervez, Affan und Lee, Dongheui (2017) Learning task-parameterized dynamic movement primitives using mixture of GMMs. Intelligent Service Robotics. Springer. doi: 10.1007/s11370-017-0235-8. ISSN 1861-2776.
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Offizielle URL: https://link.springer.com/article/10.1007/s11370-017-0235-8
Kurzfassung
Task-parameterized skill learning aims at adaptive motion encoding to new situations. While existing approaches for task-parameterized skill learning have demonstrated good adaptation within the demonstrated region, the extrapolation problem of task-parameterized skills has not been investigated enough. In this work, with the aim of good adaptation not only within the demonstrated region but also outside of the region, we propose to combine a generative model with a dynamic movement primitive by formulating learning as a density estimation problem. Moreover, for efficient learning from relatively few demonstrations, we propose to augment training data with additional incomplete data. The proposed method is tested and compared with existing works in simulations and real robot experiments. Experimental results verified its generalization in the extrapolation region.
elib-URL des Eintrags: | https://elib.dlr.de/117910/ | ||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||
Titel: | Learning task-parameterized dynamic movement primitives using mixture of GMMs | ||||||||||||
Autoren: |
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Datum: | 26 Juli 2017 | ||||||||||||
Erschienen in: | Intelligent Service Robotics | ||||||||||||
Referierte Publikation: | Ja | ||||||||||||
Open Access: | Nein | ||||||||||||
Gold Open Access: | Nein | ||||||||||||
In SCOPUS: | Ja | ||||||||||||
In ISI Web of Science: | Ja | ||||||||||||
DOI: | 10.1007/s11370-017-0235-8 | ||||||||||||
Verlag: | Springer | ||||||||||||
ISSN: | 1861-2776 | ||||||||||||
Status: | veröffentlicht | ||||||||||||
Stichwörter: | Programming by Demonstration, dynamic movement primitives, Task parameterized movement | ||||||||||||
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 - Terrestrische Assistenz-Robotik (alt) | ||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) | ||||||||||||
Hinterlegt von: | Lee, Prof. Dongheui | ||||||||||||
Hinterlegt am: | 08 Jan 2018 00:33 | ||||||||||||
Letzte Änderung: | 11 Jul 2023 08:44 |
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