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 an elastic body as a result of a deformation caused by an external force is propagated among mass points by Poisson equation. An improved Poisson model is developed for propagating the energy generated by the external force in a natural manner. A cellular neural network (CNN) model is established to solve the Poisson model for the real-time requirement of soft object deformation. A haptic virtual reality system has been established for deformation simulation with force feedback. This proposed methodology not only deals with local and large-range deformations, but also accommodates isotropic, anisotropic and inhomogeneous materials by simply modifying constitutive coefficients, as well as predicts the mechanical behaviors of living tissues.
Original language | English |
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Pages (from-to) | 445-473 |
Number of pages | 29 |
Journal | International Journal of Image and Graphics |
Volume | 6 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jul 2006 |
Keywords
- analogy systems
- CNN
- Deformation
- haptic feedback
- Poisson equation
- virtual reality