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Switched Latent Force Models for Movement Segmentation

2010

Conference Paper

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Latent force models encode the interaction between multiple related dynamical systems in the form of a kernel or covariance function. Each variable to be modeled is represented as the output of a differential equation and each differential equation is driven by a weighted sum of latent functions with uncertainty given by a Gaussian process prior. In this paper we consider employing the latent force model framework for the problem of determining robot motor primitives. To deal with discontinuities in the dynamical systems or the latent driving force we introduce an extension of the basic latent force model, that switches between different latent functions and potentially different dynamical systems. This creates a versatile representation for robot movements that can capture discrete changes and non-linearities in the dynamics. We give illustrative examples on both synthetic data and for striking movements recorded using a BarrettWAM robot as haptic input device. Our inspiration is robot motor primitives, but we expect our model to have wide application for dynamical systems including models for human motion capture data and systems biology.

Author(s): Alvarez, MA. and Peters, J. and Schölkopf, B. and Lawrence, ND.
Book Title: Advances in neural information processing systems 23
Journal: Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010
Pages: 55-63
Year: 2010
Day: 0
Editors: J Lafferty and CKI Williams and J Shawe-Taylor and RS Zemel and A Culotta
Publisher: Curran

Department(s): Empirical Inference
Research Project(s): Robot Skill Learning
Bibtex Type: Conference Paper (inproceedings)

Address: Red Hook, NY, USA
Digital: 0
Event Name: 24th Annual Conference on Neural Information Processing Systems (NIPS 2010)
Event Place: Vancouver, BC, Canada
ISBN: 978-1-617-82380-0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{6743,
  title = {Switched Latent Force Models for Movement Segmentation},
  author = {Alvarez, MA. and Peters, J. and Sch{\"o}lkopf, B. and Lawrence, ND.},
  journal = {Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010},
  booktitle = {Advances in neural information processing systems 23},
  pages = {55-63},
  editors = {J Lafferty and CKI Williams and J Shawe-Taylor and RS Zemel and A Culotta},
  publisher = {Curran},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Red Hook, NY, USA},
  year = {2010}
}