gProximity: Hierarchical GPU-based Operations for Collision and Distance Queries

dc.contributor.authorLauterbach, C.en_US
dc.contributor.authorMo, Q.en_US
dc.contributor.authorManocha, D.en_US
dc.date.accessioned2015-02-23T16:40:51Z
dc.date.available2015-02-23T16:40:51Z
dc.date.issued2010en_US
dc.description.abstractWe 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.en_US
dc.description.number2en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01611.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages419-428en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01611.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titlegProximity: Hierarchical GPU-based Operations for Collision and Distance Queriesen_US
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