Learning to Select and Generalize Striking Movements in Robot Table Tennis

Muelling, K., Kober, J., Kroemer, O. and Peters, J.
Journal Article, International Journal of Robotics Research (IJRR), Vol. 32, No. 3, pp. 263 - 279, March, 2013

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.


Learning new motor tasks from physical interactions is an important goal for both robotics and machine learning. However, when moving beyond basic skills, most monolithic machine learning approaches fail to scale. For more complex skills, methods that are tailored for the domain of skill learning are needed. In this paper, we take the task of learning table tennis as an example and present a new framework that allows a robot to learn cooperative table tennis from physical interaction with a human. The robot first learns a set of elementary table tennis hitting movements from a human table tennis teacher by kinesthetic teach-in, which is compiled into a set of motor primitives represented by dynamical systems. The robot subsequently generalizes these movements to a wider range of situations using our mixture of motor primitives approach. The resulting policy enables the robot to select appropriate motor primitives as well as to generalize between them. Finally, the robot plays with a human table tennis partner and learns online to improve its behavior. We show that the resulting setup is capable of playing table tennis using an anthropomorphic robot arm.

author = {Muelling, K. and Kober, J. and Kroemer, O. and Peters, J.},
title = {Learning to Select and Generalize Striking Movements in Robot Table Tennis},
journal = {International Journal of Robotics Research (IJRR)},
year = {2013},
month = {March},
volume = {32},
number = {3},
pages = {263 - 279},
} 2018-10-03T13:18:14-04:00