Integrating Gyroscopes into Ubiquitous Tracking Environments

D. Pustka, Manuel J. Huber, G. Klinker
{"title":"Integrating Gyroscopes into Ubiquitous Tracking Environments","authors":"D. Pustka, Manuel J. Huber, G. Klinker","doi":"10.1109/VR.2008.4480802","DOIUrl":null,"url":null,"abstract":"It is widely recognized that inertial sensors, in particular gyroscopes, can improve the latency and accuracy of orientation tracking by fusing the inertial measurements with data from other sensors. In our previous work, we introduced the concepts of spatial relationship graphs and spatial relationship patterns to formally model multi-sensor tracking setups and derive valid applications of well-known algorithms in order to infer new spatial relationships for tracking and calibration. In this work, we extend our approach by providing additional spatial relationship patterns that transform incremental rotations and add gyroscope alignment and fusion. The usefulness of the resulting tracking configurations is evaluated in two different scenarios with both inside-out and outside-in tracking.","PeriodicalId":173744,"journal":{"name":"2008 IEEE Virtual Reality Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Virtual Reality Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VR.2008.4480802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

It is widely recognized that inertial sensors, in particular gyroscopes, can improve the latency and accuracy of orientation tracking by fusing the inertial measurements with data from other sensors. In our previous work, we introduced the concepts of spatial relationship graphs and spatial relationship patterns to formally model multi-sensor tracking setups and derive valid applications of well-known algorithms in order to infer new spatial relationships for tracking and calibration. In this work, we extend our approach by providing additional spatial relationship patterns that transform incremental rotations and add gyroscope alignment and fusion. The usefulness of the resulting tracking configurations is evaluated in two different scenarios with both inside-out and outside-in tracking.
将陀螺仪集成到无处不在的跟踪环境中
惯性传感器,特别是陀螺仪,通过将惯性测量数据与其他传感器的数据融合,可以提高定位跟踪的延迟性和精度。在我们之前的工作中,我们引入了空间关系图和空间关系模式的概念来正式建模多传感器跟踪设置,并推导出已知算法的有效应用,以推断用于跟踪和校准的新空间关系。在这项工作中,我们通过提供额外的空间关系模式来扩展我们的方法,这些模式可以转换增量旋转并添加陀螺仪对齐和融合。在由内向外和由外向内跟踪的两种不同场景中评估所得到的跟踪配置的有用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信