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Computationally efficient techniques for data-driven haptic rendering

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83885

Di Luca,  M
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Multisensory Perception and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Höver, R., Di Luca, M., Szekely, G., & Harders, M. (2009). Computationally efficient techniques for data-driven haptic rendering. Proceedings of the World Haptics 2009: Third Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (WHC 2009), 39-44.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-C599-7
Zusammenfassung
Data-driven haptic rendering requires processing of raw recorded signals, which leads to high computational effort for large datasets. To achieve real-time performance, one possibility is to reduce the parameter space of the employed interpolation technique, which generally decreases the accuracy in the rendering. In this paper, we propose a method for guiding this parameter reduction to maintain high accuracy with respect to the just noticeable difference for forces. To this end, we performed a user study to estimate this perception threshold. The threshold is used to assess the final error in the rendered forces as well as for the parameter reduction process. Comparison with measured data from real object interactions confirms the accuracy of our method and highlights the reduced computational effort.