Abstract We present an algorithm for robust and efficient contact handling of deformable objects. By being aware of the internal dynamics of the colliding objects, our algorithm provides smooth rolling and sliding, stable stacking, robust impact handling, and seamless coupling of heterogeneous objects, all in a unified manner. We achieve dynamicsawareness through a constrained dynamics formulation with implicit complementarity constraints, and we present two major contributions that enable an efficient solution of the constrained dynamics problem: a time stepping algorithm that robustly ensures non‐penetration and progressively refines the formulation of constrained dynamics, and a new solver for large mixed linear complementarity problems, based on iterative constraint anticipation. We show the application of our algorithm in challenging scenarios such as multi‐layered cloth moving at high velocities, or colliding deformable solids simulated with large time steps.

The simulation of fracture leads to collision-intensive situations that call for efficient collision detection algorithms and data structures. Bounding volume hierarchies (BVHs) are a popular approach for accelerating collision detection, but they rarely see application in fracture simulations, due to the dynamic creation and deletion of geometric primitives. We propose the use of balanced trees for storing BVHs, as well as novel algorithms for dynamically restructuring them in the presence of progressive or instantaneous fracture. By paying a small loss of fitting quality compared with complete reconstruction, we achieve more than one order of magnitude speedup in the update of BVHs

A central training objective of virtual reality based surgical simulation is the removal of pathologic tissue. This necessitates stable, real-time updates of the underlying mesh representation. Within the framework of a hysteroscopy simulator, we have developed a hybrid cutting approach for tetrahedral meshes. It combines the topological update by subdivision with adjustments of the existing topology. Moreover, the mechanical and the visual model are decoupled, thus allowing different resolutions for the underlying mesh representations. With our method, we can closely approximate an arbitrary, user-defined cut surface while avoiding the creation of small or badly shaped elements, thus strongly reducing stability problems in the subsequent deformation computation. The presented approach has been integrated into a virtual reality training system for hysteroscopic interventions. The performance of the algorithm is demonstrated by examples of intra-uterine tumor ablations.

We present a novel framework for the efficient simulation and animation of discrete thin shells.Our method takes a point sampled surface as input and performs all necessary computations without intermediate triangulation.We discretize the thin shell functional using so-called fibers.Such fibers are locally embedded parametric curves crisscrossing individual point samples.In combination, they create a dense mesh representing the surface structure and connectivity for the shell computations.In particular, we utilize the fibers to approximate the differential surface operators of the thin shell functional.The polynomials underlying the fiber representation allow for a robust and fast simulation of thin shell behavior.Our method supports both elastic and plastic deformations as well as fracturing and tearing of the material.To compute surfaces with rich surface detail, we designed a multiresolution representation which maps a high-resolution surface onto a fiber network of lower resolution.This makes it possible to animate densely sampled models of very high surface complexity.While being tuned for point sampled objects, the presented framework is versatile and can also take triangle meshes or triangle soups as input.