DocumentCode :
2553955
Title :
A sparse model predictive control formulation for walking motion generation
Author :
Dimitrov, Dimitar ; Sherikov, Alexander ; Wieber, Pierre-Brice
Author_Institution :
Orebro Univ., Sweden
fYear :
2011
fDate :
25-30 Sept. 2011
Firstpage :
2292
Lastpage :
2299
Abstract :
This article presents a comparison between dense and sparse model predictive control (MPC) formulations, in the context of walking motion generation for humanoid robots. The former formulation leads to smaller, the latter one to larger but more structured optimization problem. We put an accent on the sparse formulation and point out a number of advantages that it presents. In particular, motion generation with variable center of mass (CoM) height, as well as variable discretization of the preview window, come at a negligible additional computational cost. We present a sparse formulation that comprises a diagonal Hessian matrix and has only simple bounds (while still retaining the possibility to generate motions for an omnidirectional walk). Finally, we present the results from a customized code used to solve the underlying quadratic program (QP).
Keywords :
Context; Foot; Humanoid robots; Legged locomotion; Linear matrix inequalities; Sparse matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
Conference_Location :
San Francisco, CA
ISSN :
2153-0858
Print_ISBN :
978-1-61284-454-1
Type :
conf
DOI :
10.1109/IROS.2011.6095035
Filename :
6095035
Link To Document :
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