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  Reinforcement Learning to adjust Robot Movements to New Situations

Kober, J., Oztop, E., & Peters, J. (2011). Reinforcement Learning to adjust Robot Movements to New Situations. Robotics: Science and Systems VI, 33-40.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BA64-3 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0002-061F-6
Genre: Konferenzbeitrag

Externe Referenzen

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externe Referenz:
http://www.roboticsproceedings.org/rss06/p05.pdf (Verlagsversion)
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Urheber

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 Urheber:
Kober, J1, 2, Autor           
Oztop, E, Autor
Peters, J1, 2, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Inhalt

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Schlagwörter: -
 Zusammenfassung: Many complex robot motor skills can be represented using elementary movements, and there exist efficient techniques for learning parametrized motor plans using demonstrations and self-improvement. However, in many cases, the robot currently needs to learn a new elementary movement even if a parametrized motor plan exists that covers a similar, related situation. Clearly, a method is needed that modulates the elementary movement through the meta-parameters of its representation. In this paper, we show how to learn such mappings from circumstances to meta-parameters using reinforcement learning.We introduce an appropriate reinforcement learning algorithm based on a kernelized version of the reward-weighted regression. We compare this algorithm to several previous methods on a toy example and show that it performs well in comparison to standard algorithms. Subsequently, we show two robot applications of the presented setup; i.e., the generalization of throwing movements in darts, and of hitting movements in table tennis. We show that both tasks can be learned successfully using simulated and real robots.

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Sprache(n):
 Datum: 2011-09
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 6438
DOI: 10.15607/RSS.2010.VI.005
 Art des Abschluß: -

Veranstaltung

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Titel: 2010 Robotics: Science and Systems Conference (RSS 2010)
Veranstaltungsort: Zaragoza, Spain
Start-/Enddatum: 2011-06-27 - 2011-06-30

Entscheidung

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Projektinformation

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Quelle 1

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Titel: Robotics: Science and Systems VI
Genre der Quelle: Zeitschrift
 Urheber:
Matsuoka, Y, Herausgeber
Durrant-Whyte, HF, Herausgeber
Neira, J, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: Cambridge, MA, USA : MIT Press
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 33 - 40 Identifikator: ISBN: 978-0-262-51681-5