CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements
Liu, Jinxu1,2; Gao, Wei1,2; Hu, Zhanyi1,2
2021-05-31
Conference Name2021 IEEE International Conference on Robotics and Automation (ICRA 2021)
Conference Date2021年5月31日至6月4日
Conference Place中国西安
PublisherIEEE
Abstract
Unlike loose coupling approaches and the EKF-based approaches in the literature, we propose an optimization-based visual-inertial SLAM tightly coupled with raw Global Navigation Satellite System (GNSS) measurements, a first attempt of this kind in the literature to our knowledge. More specififically, reprojection error, IMU pre-integration error and raw GNSS measurement error are jointly minimized within a sliding window, in which the asynchronism between images and raw GNSS measurements is accounted for. In addition, issues such as marginalization, noisy measurements removal, as well as tackling vulnerable situations are also addressed. Experimental results on public dataset in complex urban scenes  show that our proposed approach outperforms state-of-the-art  visual-inertial SLAM, GNSS single point positioning, as well as  a loose coupling approach, including scenes mainly containing low-rise buildings and those containing urban canyons.
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44969
Collection模式识别国家重点实验室_机器人视觉
Corresponding AuthorGao, Wei
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.School of Artificial Intelligence, University of Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Liu, Jinxu,Gao, Wei,Hu, Zhanyi. Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements[C]:IEEE,2021.
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