Toward Real-Time Scalable Rigid-Body Simulation Using GPU-Optimized Collision Detection and Response

Nak-Jun Sung and Min Hong ()
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Nak-Jun Sung: Research Institute, National Cancer Center Korea, Goyang-si 10408, Republic of Korea
Min Hong: Department of Computer Software Engineering, Soonchunhyang University, Asan-si 31538, Republic of Korea

Mathematics, 2025, vol. 13, issue 19, 1-25

Abstract: 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.

Keywords: rigid-body simulation; real-time collision detection; collision response; GPU-parallel processing (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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