Empirical Inference Conference Paper 2010

A biomimetic approach to robot table tennis

Although human beings see and move slower than table tennis or baseball robots, they manage to outperform such robot systems. One important aspect of this better performance is the human movement generation. In this paper, we study trajectory generation for table tennis from a biomimetic point of view. Our focus lies on generating efficient stroke movements capable of mastering variations in the environmental conditions, such as changing ball speed, spin and position. We study table tennis from a human motor control point of view. To make headway towards this goal, we construct a trajectory generator for a single stroke using the discrete movement stages hypothesis and the virtual hitting point hypothesis to create a model that produces a human-like stroke movement. We verify the functionality of the trajectory generator for a single forehand stroke both in a simulation and using a real Barrett WAM.

Author(s): Mülling, K. and Kober, J. and Peters, J.
Journal: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
Pages: 1921-1926
Year: 2010
Month: October
Day: 0
Publisher: IEEE
Bibtex Type: Conference Paper (inproceedings)
Address: Piscataway, NJ, USA
DOI: 10.1109/IROS.2010.5650305
Event Name: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
Event Place: Taipei, Taiwan
Digital: 0
Electronic Archiving: grant_archive
Institution: Institute of Electrical and Electronics Engineers
ISBN: 978-1-424-46675-7
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@inproceedings{6641,
  title = {A biomimetic approach to robot table tennis},
  journal = {Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)},
  abstract = {Although human beings see and move slower than table tennis or baseball robots, they manage to outperform such robot systems. One important aspect of this better performance is the human movement generation. In this paper, we study trajectory generation for table tennis from a biomimetic point of view. Our focus lies on generating efficient stroke movements capable of mastering variations in the environmental conditions, such as changing ball speed, spin and position. We study table tennis from a human motor control point of view. To make headway towards this goal, we construct a trajectory generator for a single stroke using the discrete movement stages hypothesis and the virtual hitting point hypothesis to create a model that produces a human-like stroke movement. We verify the functionality of the trajectory generator for a single forehand stroke both in a simulation and using a real Barrett WAM.},
  pages = {1921-1926},
  publisher = {IEEE},
  organization = {Max-Planck-Gesellschaft},
  institution = {Institute of Electrical and Electronics Engineers},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = oct,
  year = {2010},
  slug = {6641},
  author = {M{\"u}lling, K. and Kober, J. and Peters, J.},
  month_numeric = {10}
}