Robust and Efficient Penetration-Free Elastodynamics without Barriers

Robust and Efficient Penetration-Free Elastodynamics without Barriers

Publication: ACM Transactions on Graphics (SIGGRAPH 2026 Journal Track)

Project Website: https://simulation-intelligence.github.io/barrier-free/

arXiv Paper: https://arxiv.org/abs/2512.12151v1/

Authors

Juntian Zheng, Zhaofeng Luo, Minchen Li

Abstract

This research presents an optimization approach for simulating elastic objects without physical penetration. The method addresses efficiency challenges in existing methods by:

1. Eliminating logarithmic barrier functions that cause poorly conditioned mathematical systems
2. Resolving “time-of-impact locking” that slows collision detection in complex scenes

Key Innovations

• Novel framework using an augmented Lagrangian solver with adaptive multiplier updates instead of increasing penalty stiffness
• Constraint filtering and decay mechanism to keep the active set compact
• GPU optimization enabling up to 103x speedup over GIPC on challenging, contact-rich benchmarks

Publication Information

• Venue: ACM Transactions on Graphics (SIGGRAPH 2026 Journal Track)
• arXiv: 2512.12151v1
• Submitted: December 13, 2025
• Category: Computer Science > Graphics (cs.GR)
• DOI: https://doi.org/10.1145/3811035

Open Source

The authors have committed to open-sourcing their code and supplementary materials.