The Dynamic Cloth Simulation Performance Analysis Based on the Improved Spring-mass Model

This paper mainly introduces the improved classical spring-mass model, some satisfied spring parameters can be obtained with the data-driven strategy and computer assisted tomography technology, and if some external forces are added, we can get more realistic simulation results. Discussing the Euler algorithm, the midpoint algorithm, the Four-ord Runge-Kutta algorithm and adaptive Runge-Kutta algorithm, when they are under the same condition, it is found that each algorithm has its own characteristics, and the adaptive Runge-Kutta algorithm can make the cloth to achieve the system balance in a shorter time. This algorithm is accurate and effective, it is an ideal method to simulate flexible cloths, and it provides a new solution to realize the computer dynamic simulation of flexible cloths.

[1]  Gábor Székely,et al.  Identification of Spring Parameters for Deformable Object Simulation , 2007, IEEE Transactions on Visualization and Computer Graphics.

[2]  Xavier Provot,et al.  Deformation Constraints in a Mass-Spring Model to Describe Rigid Cloth Behavior , 1995 .

[3]  Paolo Fiorini,et al.  Calibration of mass spring models for organ simulations , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Jean Louchet,et al.  Evolutionary identification of cloth animation models , 1995 .

[5]  N. M. Thalmann,et al.  Developing simulation techniques for an interactive clothing system , 1997, Proceedings. International Conference on Virtual Systems and MultiMedia VSMM '97 (Cat. No.97TB100182).

[6]  Andrew P. Witkin,et al.  Large steps in cloth simulation , 1998, SIGGRAPH.

[7]  Hervé Delingette,et al.  Anisotropic elasticity and force extrapolation to improve realism of surgery simulation , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[8]  Gábor Székely,et al.  Mesh Topology Identification for Mass-Spring Models , 2003, MICCAI.