期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 16, 期 6, 页码 4049-4058出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2959380
关键词
Jacobian matrices; Visualization; Real-time systems; Pose estimation; Feature extraction; Dual-step marginalization; sliding window; visual-inertial odometry
类别
资金
- National Key R&D Program of China [2017YFC0803300]
- National Science Foundation of China [61773393, U1813205, TII-19-1429]
This article presents a sliding widow-based visual-inertial odometry to deal with the micro air vehicle (MAV) pose estimation problem. Errors caused by inertial measurement unit (IMU) preintegration, visual landmarks reprojection, and marginalization, are unified into a nonlinear residual minimization framework. Furthermore, a dual-step marginalization method has been proposed to increase the computational efficiency. Experiments have been conducted on publicly available datasets, as well as customized handheld and MAV platform, where state-of-the-art approaches have served as the baselines for comparison. According to the results, the proposed method has a comparative accuracy, which can run in real-time on an onboard minicomputer.
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