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Kimera-VIO is a library for accurate state estimation from stereo or mono cameras and IMU data. It can also generate 3D meshes and perform loop closure detection with GTSAM.
This guide covers setting up SLAM projects, on-device SuperPoint for localization, and syncing frames with IMU messages for accurate mapping and navigation.
SLAM, VIO, RANSAC, Dynamic Environment, Degenerate Motion 12 1 Introduction Visual-inertial odometry (VIO) systems are crucial to many applications from virtual reality (VR), augmented reality (AR), drones, autonomous driving, and robotics. Most of the visual-inertial SLAM systems rely on VIO technique for sensor fusion and state estimation.
VIO-mono The average parallax of tracked features between current frame and the latest keyframe is beyond a certain threshold. To avoid rotation-only parallax, rotation compensation via IMU integration is used. The number of tracked features goes below a certain threshold. ORB-SLAM (Surval of the fittest strategy) Time from last keyframe > 0.5s.
GO-SLAM optimizes local pose estimation by leveraging available GPS signals and inertial data from visual-inertial odometry (VIO). The system incorporates kinodynamic path search, which employs a hierarchical, time-optimal trajectory planning method to ensure comprehensive coverage.
This method, known as VIO (visual-inertial odometry), improves estimation performance when there is a lack of distinctive features in the scene to track motion visually. SLAM (simultaneous localization and mapping) is built on top of VIO, creating a map of key points that can be used to determine if an area is previously seen.
Visual odometry (VIO) and SLAM use sensors to simulate position, movement and environment in virtual worlds. Learn more about how VIO and SLAM work.
We present HybVIO, a novel hybrid approach for combining filtering-based visual-inertial odometry (VIO) with optimization-based SLAM. The core of our method is highly robust, independent VIO with improved IMU bias modeling, outlier rejection, stationarity detection, and feature track selection, which is adjustable to run on embedded hardware. Long-term consistency is achieved with a loosely ...
This is a compact and fully integrated VIO-SLAM (Visual-Inertial Odometry + SLAM) solution, designed for real-time perception and localization tasks in robotics and research applications.
Explore the key differences between SLAM and VIO in spatial tracking technologies. Learn about their unique approaches, applications, and performance considerations for developers and tech enthusiasts.