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Autonomous Motion Conference Paper 2011

Movement segmentation using a primitive library

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Autonomous Motion
Franzi Meier
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Autonomous Motion
Stefan Schaal
  • Director

Segmenting complex movements into a sequence of primitives remains a difficult problem with many applications in the robotics and vision communities. In this work, we show how the movement segmentation problem can be reduced to a sequential movement recognition problem. To this end, we reformulate the orig-inal Dynamic Movement Primitive (DMP) formulation as a linear dynamical sys-tem with control inputs. Based on this new formulation, we develop an Expecta-tion-Maximization algorithm to estimate the duration and goal position of a par-tially observed trajectory. With the help of this algorithm and the assumption that a library of movement primitives is present, we present a movement seg-mentation framework. We illustrate the usefulness of the new DMP formulation on the two applications of online movement recognition and movement segmen-tation.

Author(s): Meier, F. and Theodorou, E. and Stulp, F. and Schaal, S.
Book Title: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011)
Year: 2011
Bibtex Type: Conference Paper (inproceedings)
Address: Sept. 25-30, San Francisco, CA
URL: http://www-clmc.usc.edu/publications/M/meier-IROS2011
Cross Ref: p10480
Electronic Archiving: grant_archive
Note: clmc

BibTex 

@inproceedings{Meier_IICIRS_2011,
  title = {Movement segmentation using a primitive library},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011)},
  abstract = {Segmenting complex movements into a sequence of primitives remains a difficult problem with many applications in the robotics and vision communities. In this work, we show how the movement segmentation problem can be reduced to a sequential movement recognition problem. To this end, we reformulate the orig-inal Dynamic Movement Primitive (DMP) formulation as a linear dynamical sys-tem with control inputs.  Based on this new formulation, we develop an Expecta-tion-Maximization algorithm to estimate the duration and goal position of a par-tially observed trajectory. With the help of this algorithm and the assumption that a library of movement primitives is present, we present a movement seg-mentation framework. We illustrate the usefulness of the new DMP formulation on the two applications of online movement recognition and movement segmen-tation.},
  address = {Sept. 25-30, San Francisco, CA},
  year = {2011},
  note = {clmc},
  slug = {meier_iicirs_2011},
  author = {Meier, F. and Theodorou, E. and Stulp, F. and Schaal, S.},
  crossref = {p10480},
  url = {http://www-clmc.usc.edu/publications/M/meier-IROS2011}
}