Calinon, S. (2016)
Stochastic learning and control in multiple coordinate systems
Intl Workshop on Human-Friendly Robotics (HFR).


A probabilistic interpretation of model predictive control is presented, enabling extensions to multiple coordinate systems. The resulting controller follows a minimal intervention principle, by learning and retrieving invariant motion patterns through the coordination of several frames of reference. When combined with a generative model, the approach can be used in various human-robot applications that are discussed in the paper.

Bibtex reference

  author="Calinon, S.",
  title="Stochastic learning and control in multiple coordinate systems",
  booktitle="Intl Workshop on Human-Friendly Robotics",
  address="Genova, Italy"
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