1 research outputs found
Efficient Penetration Depth Computation between Rigid Models using Contact Space Propagation Sampling
We present a novel method to compute the approximate global penetration depth
(PD) between two non-convex geometric models. Our approach consists of two
phases: offline precomputation and run-time queries. In the first phase, our
formulation uses a novel sampling algorithm to precompute an approximation of
the high-dimensional contact space between the pair of models. As compared with
prior random sampling algorithms for contact space approximation, our
propagation sampling considerably speeds up the precomputation and yields a
high quality approximation. At run-time, we perform a nearest-neighbor query
and local projection to efficiently compute the translational or generalized
PD. We demonstrate the performance of our approach on complex 3D benchmarks
with tens or hundreds of thousands of triangles, and we observe significant
improvement over previous methods in terms of accuracy, with a modest
improvement in the run-time performance.Comment: 10 pages. add the acknowledgemen