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R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
We propose a novel LiDAR-InertialVisual sensor fusion framework termed RLIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. RLIVE is contained of two subsystems, the LiDAR-inertial odometry (LIO) and visual-inertial odometry (VIO).
2021: Jiarong Lin, Fu Zhang
https://arxiv.org/pdf/2109.07982v1.pdf
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By Rob
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We propose a novel LiDAR-InertialVisual sensor fusion framework termed RLIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. RLIVE is contained of two subsystems, the LiDAR-inertial odometry (LIO) and visual-inertial odometry (VIO).
2021: Jiarong Lin, Fu Zhang
https://arxiv.org/pdf/2109.07982v1.pdf