@inproceedings{5414,
  title = {Learning Perceptual Coupling for Motor Primitives},
  journal = {Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2008)},
  booktitle = {IROS 2008},
  abstract = {Dynamic system-based motor primitives [1] have
  enabled robots to learn complex tasks ranging from Tennisswings
  to locomotion. However, to date there have been only
  few extensions which have incorporated perceptual coupling to
  variables of external focus, and, furthermore, these modifications
  have relied upon handcrafted solutions. Humans learn how
  to couple their movement primitives with external variables.
  Clearly, such a solution is needed in robotics.
  In this paper, we propose an augmented version of the dynamic
  systems motor primitives which incorporates perceptual coupling
  to an external variable. The resulting perceptually driven motor
  primitives include the previous primitives as a special case and
  can inherit some of their interesting properties. We show that
  these motor primitives can perform complex tasks such as Ball-in-a-Cup or Kendama task even with large variances in the initial
  conditions where a skilled human player would be challenged. For
  doing so, we initialize the motor primitives in the traditional way
  by imitation learning without perceptual coupling. Subsequently,
  we improve the motor primitives using a novel reinforcement
  learning method which is particularly well-suited for motor
  primitives.},
  pages = {834-839},
  publisher = {IEEE Service Center},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = sep,
  year = {2008},
  author = {Kober, J. and Mohler, B. and Peters, J.},
  doi = {10.1109/IROS.2008.4650953},
  month_numeric = {9}
}