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  Learning Movement Primitives

Schaal, S., Peters, J., Nakanishi, J., & Ijspeert, A. (2005). Learning Movement Primitives. In P. Dario, & R. Chatila (Eds.), Robotics Research: The Eleventh International Symposium (pp. 561-572). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D4BD-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-0E20-8
Genre: Conference Paper

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https://link.springer.com/content/pdf/10.1007%2F11008941_60.pdf (Publisher version)
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 Creators:
Schaal, S1, Author           
Peters, J1, Author           
Nakanishi, J, Author
Ijspeert, A, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: 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 b
y 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.

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 Dates: 2005-08
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/11008941_60
BibTex Citekey: 5055
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Title: 11th International Symposium on Robotics Research (ISRR 2003)
Place of Event: Siena, Italy
Start-/End Date: 2003-10-19 - 2003-10-22

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Title: Robotics Research: The Eleventh International Symposium
Source Genre: Proceedings
 Creator(s):
Dario, P, Editor
Chatila, R, Editor
Affiliations:
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 561 - 572 Identifier: ISBN: 3-540-23214-1

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Title: Springer Tracts in Advanced Robotics
Source Genre: Series
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Pages: - Volume / Issue: 15 Sequence Number: - Start / End Page: - Identifier: -