中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Error aware multiple vertical planes based visual localization for mobile robots in urban environments

文献类型:期刊论文

作者Li HF(李海丰); Wang HP(王鸿鹏); Liu JT(刘景泰)
刊名Science China Information Sciences
出版日期2015
卷号58期号:3页码:1-14
关键词visual localization multiple vertical planes error aware, convex optimization, satellite images urban environment, mobile robot
ISSN号1674-733X
产权排序2
通讯作者李海丰 ; 王鸿鹏
中文摘要A novel error-aware visual localization method is proposed that utilizes vertical planes, such as vertical building facades in urban areas as landmarks. Vertical planes, reconstructed from coplanar vertical lines, are robust high-level features if compared with point features or line features. Firstly, the error models of vertical lines and vertical planes are built, where maximum likelihood estimation (MLE) is employed to estimate all vertical planes from coplanar vertical lines. Then, the closed-form representation of camera location error variance is derived. Finally, the minimum variance camera pose estimation is formulated into a convex optimization problem, and the weight for each vertical plane is obtained by solving this well-studied problem. Experiments are carried out and the results show that the proposed localization method has an accuracy of about 2 meters, at par with commercial GPS operating in open environments.
收录类别SCI ; EI ; CSCD
语种英语
WOS记录号WOS:000349811500012
源URL[http://ir.sia.cn/handle/173321/17290]  
专题沈阳自动化研究所_机器人学研究室
推荐引用方式
GB/T 7714
Li HF,Wang HP,Liu JT. Error aware multiple vertical planes based visual localization for mobile robots in urban environments[J]. Science China Information Sciences,2015,58(3):1-14.
APA Li HF,Wang HP,&Liu JT.(2015).Error aware multiple vertical planes based visual localization for mobile robots in urban environments.Science China Information Sciences,58(3),1-14.
MLA Li HF,et al."Error aware multiple vertical planes based visual localization for mobile robots in urban environments".Science China Information Sciences 58.3(2015):1-14.

入库方式: OAI收割

来源:沈阳自动化研究所

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