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Learning motor primitives for robotics

2009

Conference Paper

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The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the application of machine learning techniques in this context. Employing an improved form of the dynamic systems motor primitives originally introduced by Ijspeert et al. [2], we show how both discrete and rhythmic tasks can be learned using a concerted approach of both imitation and reinforcement learning. For doing so, we present both learning algorithms and representations targeted for the practical application in robotics. Furthermore, we show that it is possible to include a start-up phase in rhythmic primitives. We show that two new motor skills, i.e., Ball-in-a-Cup and Ball-Paddling, can be learned on a real Barrett WAM robot arm at a pace similar to human learning while achieving a significantly more reliable final performance.

Author(s): Kober, J. and Peters, J.
Journal: Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA 2009)
Pages: 2112-2118
Year: 2009
Month: May
Day: 0
Publisher: IEEE Service Center

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1109/ROBOT.2009.5152577
Event Name: IEEE International Conference on Robotics and Automation (ICRA ’09)
Event Place: Kobe, Japan

Address: Piscataway, NJ, USA
Digital: 0
Institution: Institute of Electrical and Electronics Engineers
ISBN: 978-1-4244-2788-8
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{5661,
  title = {Learning motor primitives for robotics},
  author = {Kober, J. and Peters, J.},
  journal = {Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA 2009)},
  pages = {2112-2118},
  publisher = {IEEE Service Center},
  organization = {Max-Planck-Gesellschaft},
  institution = {Institute of Electrical and Electronics Engineers},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = may,
  year = {2009},
  month_numeric = {5}
}