This paper presents a new methodology from the standpoint of energy propagation for
real-time and nonlinear modelling of deformable objects. It formulates the deformation
process of a soft object as a process of energy propagation, in which the mechanical
load applied to the object to cause deformation is viewed as the equivalent potential
energy based on the law of conservation of energy and is further propagated among
masses of the object based on the nonlinear Poisson propagation. Poisson propagation
of mechanical load in conjunction with non-rigid mechanics of motion is developed
to govern the dynamics of soft object deformation. Further, these two governing processes
are modelled with cellular neural networks to achieve real-time computational performance.
A prototype simulation system with a haptic device is implemented for real-time simulation
of deformable objects with haptic feedback. Simulations, experiments as well as comparisons
demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship,
capable of modelling large-range deformation. It can also accommodate homogeneous,
anisotropic and heterogeneous materials by simply changing the constitutive coefficient
value of mass points.