Kinetic Separation Lists for Continuous Collision Detection of Deformable Objects

Abstract

We present a new acceleration scheme for continuous collision detection of objects under arbitrary deformations. Both pairwise and self collision detection are presented. This scheme is facilitated by a new acceleration data structure, the kinetic separation list. The event-based approach of our kinetic separation list enables us to transform the continuous problem into a discrete one. Thus, the number of updates of the bounding volume hierarchies as well as the number of bounding volume checks can be reduced significantly. We performed a comparison of our kinetic approaches with the classical swept volume algorithm. The results show that our algorithm performs up to fifty times faster in practically relevant scenarios.