Cellular neural network based deformation simulation with haptic force feedback
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This paper presents a new methodology fordeformable object modelling by drawing an analogybetween cellular neural network (CNN) and elasticdeformation. The potential energy stored in an elasticbody as a result of a deformation caused by anexternal force is propagated among mass points by thenon-linear CNN activity. An improved CNN model isdeveloped for propagating the energy generated bythe external force on the object surface in the naturalmanner of Poisson equation. The proposedmethodology models non-linear materials with nonlinearCNN rather than geometric non-linearity in themost existing deformation methods. It can not onlydeal with large-range deformations, but it can alsoaccommodate isotropic, anisotropic andinhomogeneous materials by simply modifyingconstitutive constants.
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