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PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features
He, Yijia1,2; Zhao, Ji3; Guo, Yue1,2; He, Wenhao1; Yuan, Kui1
Source PublicationSENSORS
2018-04-01
Volume18Issue:4
SubtypeArticle
AbstractTo address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point-line visual-inertial odometry (PL-VIO), a tightly-coupled monocular visual-inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plucker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only.
KeywordSensor Fusion Visual-inertial Odometry Tightly-coupled Point And Line Features
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.3390/s18041159
WOS KeywordSIMULTANEOUS LOCALIZATION ; KALMAN FILTER ; NAVIGATION ; SLAM ; OPTIMIZATION ; MOTION
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61421004)
WOS Research AreaChemistry ; Electrochemistry ; Instruments & Instrumentation
WOS SubjectChemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS IDWOS:000435574800231
Citation statistics
Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21818
Collection智能制造技术与系统研究中心_智能机器人
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.ReadSense Ltd, Shanghai 200040, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
He, Yijia,Zhao, Ji,Guo, Yue,et al. PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features[J]. SENSORS,2018,18(4).
APA He, Yijia,Zhao, Ji,Guo, Yue,He, Wenhao,&Yuan, Kui.(2018).PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features.SENSORS,18(4).
MLA He, Yijia,et al."PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features".SENSORS 18.4(2018).
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