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# R-VIO
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R-VIO is an efficient, lightweight, **robocentric visual-inertial odometry** algorithm for consistent 3D motion tracking using only a monocular camera and a 6-axis IMU. Different from standard world-centric VINS algorithms which directly estimate absolute motion of the sensing platform with respect to a fixed, gravity-aligned, global frame of reference, R-VIO estimates the relative motion of higher accuracy with respect to a moving local frame (for example, IMU frame) and updates the global pose (orientation and position) estimate through composition. This algorithm is developed with the robocentric sliding-window filtering-based VIO framework that we originally proposed in our *IROS2018* paper and further extended in our recent *IJRR* paper:
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R-VIO is an efficient, lightweight, **robocentric visual-inertial odometry** algorithm for consistent 3D motion tracking using only a monocular camera and a 6-axis IMU. Different from standard world-centric VINS algorithms which directly estimate absolute motion of the sensing platform with respect to a fixed, gravity-aligned, global frame of reference, R-VIO estimates the relative motion of higher accuracy with respect to a moving, local frame (for example, IMU frame) and updates global pose (orientation and position) estimate through composition. This code is developed with the robocentric sliding-window filtering-based VIO framework that was originally proposed in our *IROS2018* paper and further extended in our recent *IJRR* paper:
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- Zheng Huai and Guoquan Huang, **Robocentric visual-inertial odometry**, *The International Journal of Robotics Research (IJRR)*, July 2019: [here](https://journals.sagepub.com/doi/10.1177/0278364919853361).
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