Robust and Efficient Penetration-Free Elastodynamics without Barriers

TL;DR

This paper presents a barrier-free elastodynamics simulation framework that improves efficiency and robustness by avoiding traditional barrier functions and TOI locking, enabling faster and more stable contact-rich simulations.

Contribution

We propose a novel second-order constrained optimization framework with an augmented Lagrangian solver that eliminates TOI locking and improves active-set exploration in elastodynamics simulations.

Findings

Achieves up to 103x speedup over GIPC on challenging benchmarks.

Maintains robustness and accuracy without barrier functions.

Effectively handles contact-rich scenarios with fewer Newton iterations.

Abstract

We introduce a barrier-free optimization framework for non-penetration elastodynamic simulation that matches the robustness of Incremental Potential Contact (IPC) while overcoming its two primary efficiency bottlenecks: (1) reliance on logarithmic barrier functions to enforce non-penetration constraints, which leads to ill-conditioned systems and significantly slows down the convergence of iterative linear solvers; and (2) the time-of-impact (TOI) locking issue, which restricts active-set exploration in collision-intensive scenes and requires a large number of Newton iterations. We propose a novel second-order constrained optimization framework featuring a custom augmented Lagrangian solver that avoids TOI locking by immediately incorporating all requisite contact pairs detected via CCD, enabling more efficient active-set exploration and leading to significantly fewer Newton iterations. By adaptively updating Lagrange multipliers rather than increasing penalty stiffness, our method prevents stagnation at zero TOI while maintaining a well-conditioned system. We further introduce a constraint filtering and decay mechanism to keep the active set compact and stable, along with a theoretical justification of our method's finite-step termination and first-order time integration accuracy under a cumulative TOI-based termination criterion. A comprehensive set of experiments demonstrates the efficiency, robustness, and accuracy of our method. With a GPU-optimized simulator design, our method achieves an up to 103x speedup over GIPC on challenging, contact-rich benchmarks - scenarios that were previously tractable only with barrier-based methods. Our code and data will be open-sourced.