Dynamics identification for enhanced haptic display in VR-based training platforms

D. Bi; You Fu Li; G. L. Wang

doi:10.1117/12.497755

1 April 2003 Dynamics identification for enhanced haptic display in VR-based training platforms

D. Bi, You Fu Li, G. L. Wang

Proceedings Volume 4756, Third International Conference on Virtual Reality and Its Application in Industry; (2003) https://doi.org/10.1117/12.497755
Event: Third International Conference on Virtual Reality and Its Application in Industry, 2002, Hangzhou, China

Abstract

Current VR systems mainly use geometric models, which has proved to be insufficient to provide the haptic display capability needed in many applications such as surgery training. Physics based dynamic models play a crucial role in this respect, e.g. for realistic haptic display of the operating feel via Virtual Reality (VR) systems. Such physics based models are desirably obtained via experimental identification. However, traditional dynamics identification methods normally require very large sized training data sets, which maybe difficult to meet in practical applications. This paper presents a method for identifying dynamics models using Support Vector Machines (SVM) regression algorithm which is more effective than traditional methods for high dimensional sparse training data. This method can be used as a generic learning machine or as a special learning technique that can make full use of the known dynamics structure knowledge. The experimental results show the application of our method identifying friction models for realistic haptic display.

Citation Download Citation

D. Bi, You Fu Li, and G. L. Wang "Dynamics identification for enhanced haptic display in VR-based training platforms", Proc. SPIE 4756, Third International Conference on Virtual Reality and Its Application in Industry, (1 April 2003); https://doi.org/10.1117/12.497755

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