Toward Real-Time Scalable Rigid-Body Simulation Using GPU-Optimized Collision Detection and Response Article Swipe
We propose a GPU-parallelized collision-detection and response framework for rigid-body dynamics, designed to efficiently handle densely populated 3D simulations in real time. The method combines explicit Euler time integration with a hierarchical Octree–AABB collision-detection scheme, enabling early pruning and localized refinement of contact checks. To resolve collisions, we employ a two-step response algorithm that integrates non-penetration correction and impulse-based velocity updates, stabilized through smoothing, clamping, and bias mechanisms. The framework is fully implemented within Unity3D using compute shaders and optimized GPU kernels. Experiments across multiple mesh models and increasing object counts demonstrate that the proposed hierarchical configuration significantly improves scalability and frame stability compared to conventional flat AABB methods. In particular, a two-level hierarchy achieves the best trade-off between spatial resolution and computational cost, maintaining interactive frame rates (≥30 fps) under high-density scenarios. These results suggest the practical applicability of our method to real-time simulation systems involving complex collision dynamics.
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Metadata
- Type
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- Landing Page
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All OpenAlex metadata
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https://openalex.org/W4415008618Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/math13193230Digital Object Identifier
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Toward Real-Time Scalable Rigid-Body Simulation Using GPU-Optimized Collision Detection and ResponseWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-09Full publication date if available
- Authors
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Nak-Jun Sung, Min HongList of authors in order
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https://doi.org/10.3390/math13193230Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3390/math13193230Direct OA link when available
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0Total citation count in OpenAlex
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23Number of works referenced by this work
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