A POISSON-BASED METHODOLOGY FOR DEFORMABLE OBJECT SIMULATION

Y. Zhong, B. Shirinzadeh, G. Alici, and J. Smith

Keywords

Deformation, soft objects, poisson equation, cellular neural network,analogy systems

Abstract

This paper presents a new methodology for the deformation of soft objects by drawing an analogy between Poisson equation and elastic deformation. The potential energy stored in a soft body as a result of a deformation caused by an external force is propagated among mass points by Poisson equation. The novelty of the methodology is that Poisson-based techniques are established to propagate the energy generated by the external force and to extrapolate the internal forces of a deformed object. A cellular neural network model is established to solve the Poisson model for the real-time requirement of soft object deformation. This proposed methodology not only deals with large-range deformations, but also accommodates isotropic, anisotropic and inhomogeneous materials by simply modifying constitutive coefficients.

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