基于有限元法的可变形物体碰撞检测的快速接触面积计算

P. Shrivastava, Sukhendu Das
{"title":"基于有限元法的可变形物体碰撞检测的快速接触面积计算","authors":"P. Shrivastava, Sukhendu Das","doi":"10.1109/NCVPRIPG.2013.6776197","DOIUrl":null,"url":null,"abstract":"In case of detection and analysis of deformation in collision scenarios, using a method based on area of contact instead of a point of contact generates numerically stable impulse forces. Area of contact improves the stability of control algorithms, but it is often associated with high computational cost. In this paper, we alleviate this problem by proposing a novel algorithm for collision detection of a deformable mesh against rigid structures. We reuse the data structures maintained for elastic force computations in the FEM, for the purpose of collision detection. Parallel constructs on GPU using reduced model make the simulations interactive even for meshes with thousands of elements. Since we don't maintain any additional complex structure for keeping track of the deformable body at each iteration, we significantly reduce the usage of GPU memory bandwidth. Efficiency of our method is illustrated by reporting high culling efficiency on various tests.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fast area of contact computation for collision detection of a deformable object using FEM\",\"authors\":\"P. Shrivastava, Sukhendu Das\",\"doi\":\"10.1109/NCVPRIPG.2013.6776197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In case of detection and analysis of deformation in collision scenarios, using a method based on area of contact instead of a point of contact generates numerically stable impulse forces. Area of contact improves the stability of control algorithms, but it is often associated with high computational cost. In this paper, we alleviate this problem by proposing a novel algorithm for collision detection of a deformable mesh against rigid structures. We reuse the data structures maintained for elastic force computations in the FEM, for the purpose of collision detection. Parallel constructs on GPU using reduced model make the simulations interactive even for meshes with thousands of elements. Since we don't maintain any additional complex structure for keeping track of the deformable body at each iteration, we significantly reduce the usage of GPU memory bandwidth. Efficiency of our method is illustrated by reporting high culling efficiency on various tests.\",\"PeriodicalId\":436402,\"journal\":{\"name\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCVPRIPG.2013.6776197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在碰撞变形的检测和分析中,使用基于接触面积而不是接触点的方法可以产生数值稳定的冲力。接触面积提高了控制算法的稳定性,但往往伴随着较高的计算成本。在本文中,我们通过提出一种新的算法来缓解这个问题,该算法用于变形网格与刚性结构的碰撞检测。为了碰撞检测的目的,我们重用了FEM中弹性力计算的数据结构。采用简化模型在GPU上并行构建,使仿真即使对具有数千个单元的网格也具有交互性。因为我们不需要在每次迭代中维护任何额外的复杂结构来跟踪可变形的物体,所以我们大大减少了GPU内存带宽的使用。通过报告各种测试的高剔除效率来说明我们的方法的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Fast area of contact computation for collision detection of a deformable object using FEM
In case of detection and analysis of deformation in collision scenarios, using a method based on area of contact instead of a point of contact generates numerically stable impulse forces. Area of contact improves the stability of control algorithms, but it is often associated with high computational cost. In this paper, we alleviate this problem by proposing a novel algorithm for collision detection of a deformable mesh against rigid structures. We reuse the data structures maintained for elastic force computations in the FEM, for the purpose of collision detection. Parallel constructs on GPU using reduced model make the simulations interactive even for meshes with thousands of elements. Since we don't maintain any additional complex structure for keeping track of the deformable body at each iteration, we significantly reduce the usage of GPU memory bandwidth. Efficiency of our method is illustrated by reporting high culling efficiency on various tests.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Image deblurring in super-resolution framework Surface fitting in SPECT imaging useful for detecting Parkinson's Disease and Scans Without Evidence of Dopaminergic Deficit Automatic number plate recognition system using modified stroke width transform UKF based multi-component phase estimation in digital holographic Moiré Feature preserving anisotropic diffusion for image restoration
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1