Adaptive and embedded deformation model: An approach to haptic interaction with complex inhomogeneous elastic objects

We propose a novel approach to haptic interact with complex inhomogeneous elastic objects like organs. In surgery simulations, representation of complex inhomogeneous elastic objects which have various physical properties and geometries is required. Also, consideration of geometric nonlinearity is required. At present, in order to simulate such objects correctly, we have to use the nonlinear FEM model with high resolution meshes. Furthermore, higher update rate (about from several hundred [Hz]) is required for stable force feedback. Therefore, computational cost becomes problem. In this paper, to solve this problem, we propose an adaptive and embedded deformation model. This approach uses both an online re-mesh deformation model and a corotational FEM model together. Our approach can update an inverse of a global stiffness matrix of a corotational FEM model quickly during the online remeshing (tetrahedron subdivision/simplification). In addition, an efficient computation algorithm by GPU is also proposed. We implemented this approach into our prototype surgery simulation system, and then we performed evaluation experiments to verify the feasibility and effectiveness of our approach.