Soft Articulated Characters in Projective Dynamics


Jing Li
University of Utah
 
Tiantian Liu
Microsoft Research Asia
 
Ladislav Kavan
University of Utah
 


Our method can be used to simulate a deformable Thorndyke model with internal bones and external rigid parts like the horns, teeth and nails.



Abstract

We propose a fast and robust solver to simulate continuum-based deformable models with constraints, in particular, rigid-body and joint constraints useful for soft articulated characters. Our method embeds the degrees of freedom of both articulated rigid bodies and deformable bodies in one unified constrained optimization problem, thus coupling the deformable and rigid bodies. Inspired by Projective Dynamics which is a fast numerical solver to simulate deformable objects, we also propose a novel local/global solver that takes full advantage of the pre-factorized system matrices to accelerate the solve of our constrained optimization problem. Therefore, our method can efficiently simulate character models, with rigid-body parts (bones) being correctly coupled with deformable parts (flesh). Our method is stable because backward Euler time integration is applied to both rigid and deformable degrees of freedom. Our unified optimization problem is rigorously derived from constrained Newtonian mechanics. When simulating only articulated rigid bodies as a special case, our method converges to the state-of-the-art rigid body simulators.






Publication

Jing Li, Tiantian Liu, Ladislav Kavan. Soft Articulated Characters in Projective Dynamics. IEEE Transactions on Visualization and Computer Graphics, 2020.    


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Acknowledgements

We thank Eftychios Sifakis for many inspiring discussions. We also thank Yasmin Down for Thorndyke modelling, and Henry Rietra for snail modelling, Dimitar Dinev for proofreading. This work was supported in part by National Key R&D Program of China [grant number 2018YB1403900] and the National Science Foundation under Grant Numbers IIS1617172, IIS-1622360 and IIS-1764071. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also gratefully acknowledge the support of Activision, Adobe, and hardware donation from NVIDIA Corporation.