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A biomimetic approach to robot table tennis

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84097

Mülling,  K
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84021

Kober,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84135

Peters,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Zitation

Mülling, K., Kober, J., & Peters, J. (2010). A biomimetic approach to robot table tennis. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010) (pp. 1921-1926). Piscataway, NJ, USA: IEEE.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-BDE4-9
Zusammenfassung
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.