Realtime Simulation of Thin-Shell Deformable Materials Using CNN-Based Mesh Embedding

doi:10.1109/LRA.2020.2970624

	Realtime Simulation of Thin-Shell Deformable Materials Using CNN-Based Mesh Embedding
	Tan, Qingyang 1; Pan, Zherong 2; Gao, Lin 3; Manocha, Dinesh 1
	2020-04-01
发表期刊	IEEE ROBOTICS AND AUTOMATION LETTERS
ISSN	2377-3766
卷号	5 期号:2 页码:2325-2332
摘要	We address the problem of accelerating thin-shell deformable object simulations by dimension reduction. We present a new algorithm to embed a high-dimensional configuration space of deformable objects in a low-dimensional feature space, where the configurations of objects and feature points have approximate one-to-one mapping. Our key technique is a graph-based convolutional neural network (CNN) defined on meshes with arbitrary topologies and a new mesh embedding approach based on physics-inspired loss term. We have applied our approach to accelerate high-resolution thin shell simulations corresponding to cloth-like materials, where the configuration space has tens of thousands of degrees of freedom. We show that our physics-inspired embedding approach leads to higher accuracy compared with prior mesh embedding methods. Finally, we show that the temporal evolution of the mesh in the feature space can also be learned using a recurrent neural network (RNN) leading to fully learnable physics simulators. After training our learned simulator runs 500-10000x faster and the accuracy is high enough for robot manipulation tasks.
关键词	Simulation and animation dexterous manipulation
DOI	10.1109/LRA.2020.2970624
收录类别	SCI
语种	英语
资助项目	ARO[W911NF1810313] ; ARO[W911NF1910315] ; Intel ; National Natural Science Foundation of China[61872440] ; Beijing Municipal Natural Science Foundation[L182016]
WOS研究方向	Robotics
WOS类目	Robotics
WOS记录号	WOS:000526572000030
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/14210
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Pan, Zherong
作者单位	1.Univ Maryland, Dept Comp Sci & Elect & Comp Engn, College Pk, MD 20740 USA 2.Univ N Carolina, Dept Comp Sci, Chapel Hill, NC 27514 USA 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Tan, Qingyang,Pan, Zherong,Gao, Lin,et al. Realtime Simulation of Thin-Shell Deformable Materials Using CNN-Based Mesh Embedding[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2020,5(2):2325-2332.
APA	Tan, Qingyang,Pan, Zherong,Gao, Lin,&Manocha, Dinesh.(2020).Realtime Simulation of Thin-Shell Deformable Materials Using CNN-Based Mesh Embedding.IEEE ROBOTICS AND AUTOMATION LETTERS,5(2),2325-2332.
MLA	Tan, Qingyang,et al."Realtime Simulation of Thin-Shell Deformable Materials Using CNN-Based Mesh Embedding".IEEE ROBOTICS AND AUTOMATION LETTERS 5.2(2020):2325-2332.