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Learning Movement Primitives


Conference Paper



This paper discusses a comprehensive framework for modular motor control based on a recently developed theory of dynamic movement primitives (DMP). DMPs are a formulation of movement primitives with autonomous nonlinear differential equations, whose time evolution creates smooth kinematic control policies. Model-based control theory is used to convert the outputs of these policies into motor commands. By means of coupling terms, on-line modifications can be incorporated into the time evolution of the differential equations, thus providing a rather flexible and reactive framework for motor planning and execution. The linear parameterization of DMPs lends itself naturally to supervised learning from demonstration. Moreover, the temporal, scale, and translation invariance of the differential equations with respect to these parameters provides a useful means for movement recognition. A novel reinforcement learning technique based on natural stochastic policy gradients allows a general approach of improving DMPs by trial and error learning with respect to almost arbitrary optimization criteria. We demonstrate the different ingredients of the DMP approach in various examples, involving skill learning from demonstration on the humanoid robot DB, and learning biped walking from demonstration in simulation, including self-improvement of the movement patterns towards energy efficiency through resonance tuning.

Author(s): Schaal, S. and Peters, J. and Nakanishi, J. and Ijspeert, A.
Book Title: 11th International Symposium on Robotics Research (ISRR2003)
Pages: 561-572
Year: 2004
Editors: Dario, P. and Chatila, R.
Publisher: Springer

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

DOI: 10.1007/11008941_60
Event Name: ISRR 2003
Event Place: Siena, Italy

Cross Ref: p1805
Note: clmc
URL: http://www-clmc.usc.edu/publications/S/schaal-ISRR2003.pdf


  title = {Learning Movement Primitives},
  author = {Schaal, S. and Peters, J. and Nakanishi, J. and Ijspeert, A.},
  booktitle = {11th International Symposium on Robotics Research (ISRR2003)},
  pages = {561-572},
  editors = {Dario, P. and Chatila, R.},
  publisher = {Springer},
  year = {2004},
  note = {clmc},
  crossref = {p1805},
  url = {http://www-clmc.usc.edu/publications/S/schaal-ISRR2003.pdf}