On-line real-time physics-based predictive motion control with balance recovery

In this paper, we present an on‐line real‐time physics‐based approach to motion control with contact repositioning based on a low‐dimensional dynamics model using example motion data. Our approach first generates a reference motion in run time according to an on‐line user request by transforming an...

Full description

Saved in:
Bibliographic Details
Published inComputer graphics forum Vol. 33; no. 2; pp. 245 - 254
Main Authors Han, Daseong, Noh, Junyong, Jin, Xiaogang, S. Shin, Joseph, Y. Shin, Sung
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.05.2014
Subjects
Online AccessGet full text
ISSN0167-7055
1467-8659
DOI10.1111/cgf.12323

Cover

Loading…
More Information
Summary:In this paper, we present an on‐line real‐time physics‐based approach to motion control with contact repositioning based on a low‐dimensional dynamics model using example motion data. Our approach first generates a reference motion in run time according to an on‐line user request by transforming an example motion extracted from a motion library. Guided by the reference motion, it repeatedly generates an optimal control policy for a small time window one at a time for a sequence of partially overlapping windows, each covering a couple of footsteps of the reference motion, which supports an on‐line performance. On top of this, our system dynamics and problem formulation allow to derive closed‐form derivative functions by exploiting the low‐dimensional dynamics model together with example motion data. These derivative functions and their sparse structures facilitate a real‐time performance. Our approach also allows contact foot repositioning so as to robustly respond to an external perturbation or an environmental change as well as to perform locomotion tasks such as stepping on stones effectively.
Bibliography:istex:11DFDDC024466A81A43F9C5880BCA6A36B68126C
ArticleID:CGF12323
ark:/67375/WNG-WX165Z4F-C
Supporting Information
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12323