Mixed-Degree Cubature H∞ Information Filter-Based Visual-Inertial Odometry
AbstractVisual–inertial odometry is an effective system for mobile robot navigation. This article presents an egomotion estimation method for a dual-sensor system consisting of a camera and an inertial measurement unit (IMU) based on the cubature information filter and H∞ filter. The intensity of the image was used as the measurement directly. The measurements from the two sensors were fused with a hybrid information filter in a tightly coupled way. The hybrid filter used the third-degree spherical-radial cubature rule in the time-update phase and the fifth-degree spherical simplex-radial cubature rule in the measurement-update phase for numerical stability. The robust H∞ filter was combined into the measurement-update phase of the cubature information filter framework for robustness toward non-Gaussian noises in the intensity measurements. The algorithm was evaluated on a common public dataset and compared to other visual navigation systems in terms of absolute and relative accuracy. View Full-Text
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Song, C.; Wang, X.; Cui, N. Mixed-Degree Cubature H∞ Information Filter-Based Visual-Inertial Odometry. Appl. Sci. 2019, 9, 56.
Song C, Wang X, Cui N. Mixed-Degree Cubature H∞ Information Filter-Based Visual-Inertial Odometry. Applied Sciences. 2019; 9(1):56.Chicago/Turabian Style
Song, Chunlin; Wang, Xiaogang; Cui, Naigang. 2019. "Mixed-Degree Cubature H∞ Information Filter-Based Visual-Inertial Odometry." Appl. Sci. 9, no. 1: 56.
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