Fast But Accurate: A Real-Time Hyperelastic Simulator with Robust Frictional Contact
Ziqiu Zeng1, Siyuan Luo2, Fan Shi2, Zhongkai Zhang1
1CAIR, Hong Kong 2National University of Singapore
ACM Transactions on Graphics (SIGGRAPH 2025)
Animation of Crossing Gingerbread Man: we propose a new framework for stable simulation of hyperelastic materials with nodes under large deformation and
generic contact constraints in real-time. Pulling the gingerbread man (58.5k DoFs for a single object) through the thin and irregular obstacles is simulated at
11.95ms/iteration using 5 local-global iterations per frame when maximum contact pairs are involved (800 contact constraints).
We present a GPU-friendly framework for real-time implicit simulation of elastic material in the presence of frictional contacts. The integration of hyperelasticity, non-interpenetration contact, and friction in real-time simulations presents formidable nonlinear and non-smooth problems, which are highly challenging to solve. By incorporating nonlinear complementarity conditions within the local-global framework, we achieve rapid convergence in addressing these challenges. While the structure of local-global methods is not fully GPU-friendly, our proposal of a simple yet efficient solver with sparse presentation of the system inverse enables highly parallel computing while maintaining a fast convergence rate. Moreover, our novel splitting strategy for non-smooth indicators not only amplifies overall performance but also refines the complementarity preconditioner, enhancing the accuracy of frictional behavior modeling. Through extensive experimentation, the robustness of our framework in managing real-time contact scenarios, ranging from large-scale systems and extreme deformations to non-smooth contacts and precise friction interactions, has been validated. Compatible with a wide range of hyperelastic models, our approach maintains efficiency across both low and high stiffness materials. Despite its remarkable efficiency, robustness, and generality, our method is elegantly simple, with its core contributions grounded solely on standard matrix operations.