Autonomous Motion Article 2004

Learning from demonstration and adaptation of biped locomotion

In this paper, we introduce a framework for learning biped locomotion using dynamical movement primitives based on non-linear oscillators. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like locomotion. We suggest dynamical movement primitives as a central pattern generator (CPG) of a biped robot, an approach we have previously proposed for learning and encoding complex human movements. Demonstrated trajectories are learned through movement primitives by locally weighted regression, and the frequency of the learned trajectories is adjusted automatically by a novel frequency adaptation algorithmbased on phase resetting and entrainment of coupled oscillators. Numerical simulations and experimental implementation on a physical robot demonstrate the effectiveness of the proposed locomotioncontroller.

Author(s): Nakanishi, J. and Morimoto, J. and Endo, G. and Cheng, G. and Schaal, S. and Kawato, M.
Book Title: Robotics and Autonomous Systems
Volume: 47
Number (issue): 2-3
Pages: 79-91
Year: 2004
Bibtex Type: Article (article)
URL: http://www-clmc.usc.edu/publications/N/nakanishi-RAS2004.pdf
Cross Ref: p1934
Electronic Archiving: grant_archive
Note: clmc

BibTex

@article{Nakanishi_RAS_2004,
  title = {Learning from demonstration and adaptation of biped locomotion},
  booktitle = {Robotics and Autonomous Systems},
  abstract = {In this paper, we introduce a framework for learning biped locomotion using dynamical movement primitives based on non-linear oscillators. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like locomotion. We suggest dynamical movement primitives as a central pattern generator (CPG) of a biped robot, an approach we have previously proposed for learning and encoding complex human movements. Demonstrated trajectories are learned through movement primitives by locally weighted regression, and the frequency of the learned trajectories is adjusted automatically by a novel frequency adaptation algorithmbased on phase resetting and entrainment of coupled oscillators. Numerical simulations and experimental implementation on a physical robot demonstrate the effectiveness of the proposed locomotioncontroller.},
  volume = {47},
  number = {2-3},
  pages = {79-91},
  year = {2004},
  note = {clmc},
  slug = {nakanishi_ras_2004},
  author = {Nakanishi, J. and Morimoto, J. and Endo, G. and Cheng, G. and Schaal, S. and Kawato, M.},
  crossref = {p1934},
  url = {http://www-clmc.usc.edu/publications/N/nakanishi-RAS2004.pdf}
}