Virtual subdivision for GPU based collision detection of deformable objects using a uniform grid

We present an improved uniform subdivision based discrete and continuous collision detection approach for deformable objects consisting of triangle meshes without any assumption about triangle size. A previously proposed technique using control bits can effectively eliminate redundant object pairs appearing in multiple cells, but this scheme requires the grid cell size adapted to the largest object, and efficiency tends to be severely impaired when object size varies strongly. In this paper, we discuss an approach that virtually subdivides large triangles into a number of child triangles to enable the use of a smaller, better suited cell size, resulting in a considerable decrease in the number of collision tests in the broad phase, with a corresponding reduced memory requirement. The virtual subdivision is used only for the purpose of collision detection and is recomputed each frame, with the original mesh retained for collision response and physical simulation. Our method exploits the benefits of GPU architecture to accelerate the computationally intensive task for improved performance. The results show that the method provides speedups by comparing performance with existing methods.