Data-driven on-line real-time physics-based locomotion synthesis based on low-dimensional model predictive control = 저차원 모델예측제어를 이용한 데이터 구동 온라인 실시간 물리 기반 보행 동작 생성

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 400
  • Download : 0
Predictive control is indispensable in human locomotion, in particular, locomotion steering and balance recovery. Humans perform prediction fast so as to move as intended as well as to respond to an unexpected external perturbation or environmental change on the fly. However, it is challenging in physics-based animation to make prediction as fast as humans do so that a realistic motion can be synthesized in real time according to an on-line user input. The main difficulty in on-line real-time motion control arises from the complexity and high dimensionality of the dynamics for a full-body character. In this thesis, 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. Our motion transformation method exploits biomechanical observations to improve the quality of the reference motion. 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.
Advisors
Noh, Jun-Yongresearcher노준용Shin, Sung-Yong신성용
Description
한국과학기술원 : 전산학과,
Publisher
한국과학기술원
Issue Date
2014
Identifier
591851/325007  / 020085348
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 전산학과, 2014.8, [ vi, 94 p. ]

Keywords

low-dimensional; physics-based; character animation; real-time; on-line; data-driven; motion synthesis; motion control; 보행; 모델예측제어; 저차원; 물리 기반; 캐릭터 애니메이션; 실시간; 온라인; 데이터 구동; 동작 합성; 동작 제어; locomotion; model predictive control

URI
http://hdl.handle.net/10203/197830
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=591851&flag=dissertation
Appears in Collection
CS-Theses_Ph.D.(박사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0