GAMES Webinar 2020 – 163期(仿真模拟专题) | Jiong Chen (Zhejiang University), Jiayi Eris Zhang (University of Toronto)

【GAMES Webinar 2020-163期】(仿真模拟专题)

报告嘉宾1:Jiong Chen (State Key Lab of CAD&CG, Zhejiang University)


报告题目:Cosserat Rod with rh-Adaptive Discretization


Rod-like one-dimensional elastic objects often exhibit complex behaviors which pose great challenges to the discretization method for pursuing a faithful simulation. By only moving a small portion of material points, the Eulerian-on-Lagrangian (EoL) method already shows great adaptivity to handle sharp contacts, but it is still far from enough to reproduce rich and complex geometry details arising in simulations. In this talk, I will introduce a novel method to simulate intricate Cosserat rod dynamics, which roots in the idea of using a hybrid rh-adaptive discretization approach. By extending the configuration space with dynamic material coordinates and applying a curvature-based redistribution law, our method can effectively constrain the motion of material points to resolve the underlying numerical degeneracy, while simultaneously enables discrete samplings to notably slide inside the parametric domain to account for better shape parameterization. Furthermore, to accurately respond to sharp contacts, this method also allows to insert or remove nodes online and adjust the energy stiffness to suppress possible jittering artifacts which could be excited in a stiff system. As a result of this hybrid rh-adaptive strategy, many realistic rod dynamics can be reproduced, such as excessive bending, twisting and knotting while only using a limited number of elements.


Jiong Chen now is a research assistant in Zhejiang University. Before that, he received his PhD degree in computer science from Zhejiang University in 2020, supervised by Professor Jin Huang. His major research interests are physically based simulation, including multiscale modeling and associated numerical algorithms.

报告嘉宾2:Jiayi Eris Zhang (University of Toronto)


报告题目:Complementary Dynamics


We present a novel approach to enrich arbitrary rig animations with elastodynamic secondary effects. Unlike previous methods which pit rig displacements and physical forces as adversaries against each other, we advocate that physics should complement artists’ intentions. We propose optimizing for elastodynamic displacements in the subspace orthogonal to displacements that can be created by the rig. This ensures that the additional dynamic motions do not undo the rig animation. The complementary space is highdimensional, algebraically constructed without manual oversight, and capable of rich high-frequency dynamics. Unlike prior tracking methods, we do not require extra painted weights, segmentation into fixed and free regions or tracking clusters. Our method is agnostic to the physical model and plugs into non-linear FEM simulations, geometric as-rigid-as-possible energies, or mass-spring models. Our method does not require a particular type of rig and adds secondary effects to skeletal animations, cage-based deformations, wire deformers, motion capture data, and rigid-body simulations.


Jiayi(Eris) Zhang is a senior undergraduate student at the University of Toronto, majoring in Computer Science and Mathematics. Jiayi has been an undergraduate research assistant in the Dynamic Graphics Project Lab, advised by Prof. Alec Jacobon. Her research interests include physics-based animation, geometry processing and interactive design tools for supporting creativity. She has published first-author papers at top venues on HCI and graphics, including CHI and SIGGRAPH ASIA 2020. She is a winner for Adobe Research Women-in-Technology Scholarship Award 2020 and a finalist for CRA Outstanding Undergraduate Researcher Award 2020. She also did a research internship at Adobe Research during 2020 summer.




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