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

Cited 5 time in webofscience Cited 0 time in scopus
  • Hit : 310
  • Download : 115
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.
Publisher
WILEY-BLACKWELL
Issue Date
2014-05
Language
English
Article Type
Article
Keywords

OPTIMAL FEEDBACK-CONTROL; HUMAN WALKING; CHARACTER ANIMATION; FRONTAL PLANE; LOCOMOTION; MODEL; SIMULATION; MOMENTUM

Citation

COMPUTER GRAPHICS FORUM, v.33, no.2, pp.245 - 254

ISSN
0167-7055
DOI
10.1111/cgf.12323
URI
http://hdl.handle.net/10203/189565
Appears in Collection
GCT-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 5 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0