Hu, Kai und Ott, Christian und Lee, Dongheui (2016) Learning and Generalization of Compensative Zero-Moment Point Trajectory for Biped Walking. IEEE Transactions on Robotics, 32 (3), Seiten 717-725. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TRO.2016.2553677. ISSN 1552-3098.
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Offizielle URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7484896
Kurzfassung
This paper presents an online learning framework for improving the robustness of zero-moment point (ZMP)-based biped walking controllers. The key idea is to learn a feedforward compensative ZMP (CZMP) trajectory from measured ZMP errors during repetitive walking motions by applying iterative learning control theory. The learned CZMP trajectory adjusts the reference ZMP and reduces the effect of unmodeled dynamics at the pattern-generation stage. From individual learned CZMP trajectories of typical walking parameters, we can build up a CZMP database. This database can be used for generating an initial CZMP whenever a new walking pattern is executed. A prediction from the database is done by k-nearest neighbor regression based on the Mahalonobis distance. Compared with state-of-the-art model-based methods, the proposed learning approach is model free and allows online adaptation to constant unknown disturbances. Enhanced walking robustness can be observed from reduced average ZMP error and more robust reaction against external disturbances on the DLR humanoid robot TORO.
elib-URL des Eintrags: | https://elib.dlr.de/105320/ | ||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||
Titel: | Learning and Generalization of Compensative Zero-Moment Point Trajectory for Biped Walking | ||||||||||||||||
Autoren: |
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Datum: | Juni 2016 | ||||||||||||||||
Erschienen in: | IEEE Transactions on Robotics | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Nein | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||
Band: | 32 | ||||||||||||||||
DOI: | 10.1109/TRO.2016.2553677 | ||||||||||||||||
Seitenbereich: | Seiten 717-725 | ||||||||||||||||
Verlag: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||
ISSN: | 1552-3098 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | Humanoid robot, learning control, ZMP, walking | ||||||||||||||||
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), R - Laufroboter/Lokomotion [SY] | ||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||
Institute & Einrichtungen: | Institut für Robotik und Mechatronik (ab 2013) > Analyse und Regelung komplexer Robotersysteme Institut für Robotik und Mechatronik (ab 2013) | ||||||||||||||||
Hinterlegt von: | Ott, Dr. Christian | ||||||||||||||||
Hinterlegt am: | 19 Jul 2016 09:53 | ||||||||||||||||
Letzte Änderung: | 06 Sep 2019 15:18 |
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