A real-time underwater SLAM system uses reliability-aware multi-sensor fusion and quadtree-guided 3D Gaussian mapping to maintain localization and photorealistic reconstruction during visual degradation.
Vins-mono: A robust and versatile monoc- ular visual-inertial state estimator
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The method combines a learned deformation model, continuous B-spline kinematics, and Newton's Second Law to enable accurate pose estimation and metric scale plus gravity recovery in monocular visual odometry on non-rigid platforms.
citing papers explorer
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APVI-SLAM: Real-Time Acoustic-Pressure-Visual-Inertial Localization and Photorealistic Mapping System in Complex Underwater Environment
A real-time underwater SLAM system uses reliability-aware multi-sensor fusion and quadtree-guided 3D Gaussian mapping to maintain localization and photorealistic reconstruction during visual degradation.
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Metric, inertially aligned monocular state estimation via kinetodynamic priors
The method combines a learned deformation model, continuous B-spline kinematics, and Newton's Second Law to enable accurate pose estimation and metric scale plus gravity recovery in monocular visual odometry on non-rigid platforms.