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State Estimation for a Humanoid Robot

2014

Conference Paper

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This paper introduces a framework for state estimation on a humanoid robot platform using only common proprioceptive sensors and knowledge of leg kinematics. The presented approach extends that detailed in prior work on a point-foot quadruped platform by adding the rotational constraints imposed by the humanoidâ??s flat feet. As in previous work, the proposed Extended Kalman Filter accommodates contact switching and makes no assumptions about gait or terrain, making it applicable on any humanoid platform for use in any task. A nonlinear observability analysis is performed on both the point-foot and flat-foot filters and it is concluded that the addition of rotational constraints significantly simplifies singular cases and improves the observability characteristics of the system. Results on a simulated walking dataset demonstrate the performance gain of the flat-foot filter as well as confirm the results of the presented observability analysis.

Author(s): Rotella, N. and Bloesch, M. and Righetti, L. and Schaal, S.
Book Title: Proceedings of the 2014 IEEE/RSJ Conference on Intelligent Robots and Systems
Pages: 952--958
Year: 2014

Department(s): Autonomous Motion, Movement Generation and Control
Research Project(s): State Estimation and Sensor Fusion for the Control of Legged Robots
Bibtex Type: Conference Paper (inproceedings)

Address: Chicago, IL
URL: http://www-clmc.usc.edu/publications/R/rotella-IROS2014.pdf

Links: PDF

BibTex

@inproceedings{Rotella_IROS14,
  title = {State Estimation for a Humanoid Robot},
  author = {Rotella, N. and Bloesch, M. and Righetti, L. and Schaal, S.},
  booktitle = {Proceedings of the 2014 IEEE/RSJ Conference on Intelligent Robots and Systems},
  pages = {952--958},
  address = {Chicago, IL},
  year = {2014},
  url = {http://www-clmc.usc.edu/publications/R/rotella-IROS2014.pdf}
}