CLODs: Dual Hierarchies for Multiresolution Collision Detection
Miguel A. Otaduy	otaduy@cs.unc.edu
Ming C. Lin	lin@cs.unc.edu
Creation of CLODs: (a) Initial surface; (b) Clusters of triangles; (c) Bounding volumes for each cluster (in this case AABBs); (d) Mesh simplification; (e) Bounding volume of the union of clusters, after some conditions are met.

Abstract: We present "contact levels of detail" (CLOD), a novel framework for multi-resolution collision detection. Given a polyhedral model, our algorithm automatically builds a "dual hierarchy", both a multi-resolution representation of the original model and its bounding volume hierarchy for accelerating collision queries. We have proposed various error metrics, including object-space errors, velocity dependent gap, screen-space errors and their combinations. At runtime, our algorithm uses these error metrics to select the appropriate levels of detail independently at each potential contact location. Compared to the existing exact collision detection algorithms, we observe significant performance improvement using CLODs on some benchmarks, with little degradation in the visual rendering of simulations.

 
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