A semantic reprojection method aligns nighttime thermal imagery with daytime semantic 3D maps to achieve 2.18 m bias-corrected RMSE2D localization accuracy for UAVs over 6.5 km of real-world flights.
Comparative analysis of UA V-based LiDAR and photogrammetric systems for the detection of terrain anomalies in a historical conflict landscape,
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Lights Out: A Nighttime UAV Localization Framework Using Thermal Imagery and Semantic 3D Maps
A semantic reprojection method aligns nighttime thermal imagery with daytime semantic 3D maps to achieve 2.18 m bias-corrected RMSE2D localization accuracy for UAVs over 6.5 km of real-world flights.