gProximity: Hierarchical GPU-based Operations for Collision and Distance Queries
Article first published online: 7 JUN 2010
© 2010 The Author(s) Journal compilation © 2010 The Eurographics Association and Blackwell Publishing Ltd.
Computer Graphics Forum
Volume 29, Issue 2, pages 419–428, May 2010
How to Cite
Lauterbach, C., Mo, Q. and Manocha, D. (2010), gProximity: Hierarchical GPU-based Operations for Collision and Distance Queries. Computer Graphics Forum, 29: 419–428. doi: 10.1111/j.1467-8659.2009.01611.x
- Issue published online: 7 JUN 2010
- Article first published online: 7 JUN 2010
- I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Geometric Algorithms, languages, and systems;
- I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Object hierarchies
We present novel parallel algorithms for collision detection and separation distance computation for rigid and deformable models that exploit the computational capabilities of many-core GPUs. Our approach uses thread and data parallelism to perform fast hierarchy construction, updating, and traversal using tight-fitting bounding volumes such as oriented bounding boxes (OBB) and rectangular swept spheres (RSS). We also describe efficient algorithms to compute a linear bounding volume hierarchy (LBVH) and update them using refitting methods. Moreover, we show that tight-fitting bounding volume hierarchies offer improved performance on GPU-like throughput architectures. We use our algorithms to perform discrete and continuous collision detection including self-collisions, as well as separation distance computation between non-overlapping models. In practice, our approach (gProximity) can perform these queries in a few milliseconds on a PC with NVIDIA GTX 285 card on models composed of tens or hundreds of thousands of triangles used in cloth simulation, surgical simulation, virtual prototyping and N-body simulation. Moreover, we observe more than an order of magnitude performance improvement over prior GPU-based algorithms.