@inproceedings{7f34db50c90e4d01b9d9f31cc7096b5d,
title = "Robust Monocular Visual-Inertial SLAM Using Nonlinear Optimization",
abstract = "In this paper, a robust monocular visual-inertial SLAM based on nonlinear optimization is proposed. In our method, visual feature points are assigned different information matrices according to the image pyramid layers at which the features are extracted. IMU pre-integration strategy is adopted to avoid repeated IMU integration caused by initial states change in optimization. Meanwhile, we adopted the strategies of sliding window and marginalization in order to yield higher precision of states estimation and restrict the computational complexity. Experiments are designed to compare our algorithm with MSCKF and VINS on EuRoC dataset, and the results show that our method can effectively estimate the motion and sparse map.",
keywords = "Inertial, Monocular visual, Nonlinear optimization, SLAM, State estimation",
author = "Jingyun Duo and Lei Ji and Long Zhao",
note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; Chinese Intelligent Systems Conference, CISC 2020 ; Conference date: 24-10-2020 Through 25-10-2020",
year = "2021",
doi = "10.1007/978-981-15-8450-3\_59",
language = "英语",
isbn = "9789811584497",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "560--568",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu",
booktitle = "Proceedings of 2020 Chinese Intelligent Systems Conference - Volume I",
address = "德国",
}