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Efficient Collision Detection for Brittle Fracture

Loeïz Glondu 1 Sara C. Schvartzman 2 Maud Marchal 1 Georges Dumont 1 Miguel A. Otaduy 2 
1 VR4I - Virtual Reality for Improved Innovative Immersive Interaction
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, ENS Cachan - École normale supérieure - Cachan, Inria Rennes – Bretagne Atlantique
Abstract : In complex scenes with many objects, collision detection plays a key role in the simulation performance. This is particularly true for fracture simulation, where multiple new objects are dynamically created. In this paper, we present novel algorithms and data structures for collision detection in real-time brittle fracture simulations. We build on a combination of well-known efficient data structures, namely distance fields and sphere trees, making our algorithm easy to integrate on existing simulation engines. We propose novel methods to construct these data structures, such that they can be efficiently updated upon fracture events and integrated in a simple yet effective self-adapting contact selection algorithm. Altogether, we drastically reduce the cost of both collision detection and collision response. We have evaluated our global solution for collision detection on challenging scenarios, achieving high frame rates suited for hard real-time applications such as video games or haptics. Our solution opens promising perspectives for complex brittle fracture simulations involving many dynamically created objects.
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Submitted on : Thursday, November 15, 2012 - 3:21:50 PM
Last modification on : Friday, February 4, 2022 - 3:22:39 AM
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  • HAL Id : hal-00752371, version 1


Loeïz Glondu, Sara C. Schvartzman, Maud Marchal, Georges Dumont, Miguel A. Otaduy. Efficient Collision Detection for Brittle Fracture. ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Jul 2012, Lausanne, Switzerland. ⟨hal-00752371⟩



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