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Computationally Efficient Techniques for Data-Driven Haptic Rendering

Raphael Höver, Massimiliano Di Luca, Gábor Székely, Matthias Harders
Proceedings of the World Haptics
Salt Lake City, Utah, USA, March 2009


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.

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  author = {Raphael H\"over and Massimiliano Di Luca and Gábor Székely and Matthias Harders},
  title = {Computationally Efficient Techniques for Data-Driven Haptic Rendering},
  booktitle = {Proceedings of the World Haptics},
  year = {2009},
  month = {March},
  pages = {39-44},
  keywords = {data-driven haptic rendering, virtual reality, deformable models}