Balance control through model predictive control based on capture point dynamics for biped walking robot = 포착점 동역학 기반의 모델 예측 제어를 통한 이족 보행 로봇의 균형 제어

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 6
  • Download : 0
This study proposes an online walking-pattern generation algorithm with footstep adjustment. The algorithm enables a biped walking robot to effectively recover balance following external disturbance. The external disturbance is measured as a capture-point error, and a desired zero-moment point (ZMP) is determined to compensate for the capture-point error through a capture-point control method. To follow the desired ZMP, the optimal ZMP and the position of the foot to be changed are determined through model predictive control (MPC). In the MPC, quadratic programming is implemented considering a cost function that minimizes the ZMP error, the constraints that the ZMP maintains within the support polygon, and the constraints on the varying foot positions. The proposed algorithm helps a humanoid robot (DRC-HUBO+) to regain balance following disturbance, i.e., from strong pushing or stepping on unexpected obstacles.
Advisors
Oh, Jun Horesearcher오준호researcher
Description
한국과학기술원 :기계공학과,
Publisher
한국과학기술원
Issue Date
2018
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 기계공학과, 2018.8,[vi, 92 p. :]

Keywords

zero moment point▼acapture point▼abiped walking robot▼aonline walking pattern▼amodel predictive control; 영 모멘트 점▼a포착점▼a이족 보행 로봇▼a온라인 보행 패턴▼a모델 예측 제어

URI
http://hdl.handle.net/10203/264540
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=827837&flag=dissertation
Appears in Collection
ME-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