We introduce an efficient solution to the problem of continuous collision detection (CCD) between triangle geometry and signed distance fields (SDFs). We formulate the triangle-SDF collision problem as a novel spatio-temporal local optimization that solves for the first time of impact between a triangle and an SDF isosurface. Our method offers improved robustness over point sampling methods, and outperforms recent triangle-SDF discrete collision detection (DCD) algorithms. Furthermore, a novel method for adaptively refining the potential collision points on large triangles is proposed for robust triangle-SDF collision detection with coarse meshes. This enables the use of reduced geometry for efficient simulations. We demonstrate the benefits of our approach by comparing to state-of-the-art algorithms for triangle-SDF collision detection, and showcase its effectiveness through simulations involving complex collision scenarios.
BibTeX
@article{trisdfccd2025, author = {Pelletier-Guénette, Joël and Mercier-Aubin, Alexandre and Andrews, Sheldon}, title = {Real-Time Triangle-SDF Continuous Collision Detection}, year = {2025}, journal = {Proceedings of the ACM on Computer Graphics and Interactive Techniques}, volume = {8}, number = {4}, series = {SCA ‘25} doi = {10.1145/3747862} }