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Learning and Generalization of Compensative Zero-Moment Point Trajectory for Biped Walking

Hu, Kai and Ott, Christian and Lee, Dongheui (2016) Learning and Generalization of Compensative Zero-Moment Point Trajectory for Biped Walking. IEEE Transactions on Robotics, 32 (3), pp. 717-725. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TRO.2016.2553677 ISSN 1552-3098

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Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7484896

Abstract

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.

Item URL in elib:https://elib.dlr.de/105320/
Document Type:Article
Title:Learning and Generalization of Compensative Zero-Moment Point Trajectory for Biped Walking
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Hu, KaiTUMUNSPECIFIED
Ott, ChristianChristian.Ott (at) dlr.dehttps://orcid.org/0000-0003-0987-7493
Lee, Dongheuidhlee (at) tum.deUNSPECIFIED
Date:June 2016
Journal or Publication Title:IEEE Transactions on Robotics
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:32
DOI :10.1109/TRO.2016.2553677
Page Range:pp. 717-725
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1552-3098
Status:Published
Keywords:Humanoid robot, learning control, ZMP, walking
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Terrestrische Assistenz-Robotik, R - Vorhaben Laufroboter/Lokomotion
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Analysis and Control of Advanced Robotic Systems
Institute of Robotics and Mechatronics (since 2013)
Deposited By: Ott, Dr. Christian
Deposited On:19 Jul 2016 09:53
Last Modified:06 Sep 2019 15:18

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