Abstract

This paper built an improved vascular model based on mass spring model, considering forces associated with springs elongation and bending. Meanwhile, for the improve of real-time computation, few nodes are used to build vascular model. In order to ensure vascular model is similar with biomechanics properties of real vascular, using Gaussian Processes to optimize parameters of model. Parameter set which can make model stable is obtained by Gaussian Process Classification and optimal parameter configuration is found by Gaussian Process Regression. A method is proposed for touch detection and force distribution between vascular model and virtual instrument. The method has been implemented in a system including a force feedback device by experiment.

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