Lights Out: A Nighttime UAV Localization Framework Using Thermal Imagery and Semantic 3D Maps

• URL: http://arxiv.org/abs/2604.26201v1
• Date: Wed, 29 Apr 2026 01:08:50 GMT
• Title: Lights Out: A Nighttime UAV Localization Framework Using Thermal Imagery and Semantic 3D Maps
• Abstract summary: This work presents a semantic reprojection framework for map-relative nighttime UAV localization.<n>Rather than relying on appearance-based correspondence, localization is formulated in a shared semantic domain.<n>System achieves a semantic bias-corrected RMSE2D of 2.18 m and a median RMSE2D of 1.52 m.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Reliable backup localization for unmanned aerial vehicles (UAVs) operating in GNSS-denied nighttime conditions remains an open challenge due to the severe modality gap between daytime RGB maps and nighttime thermal imagery. This work presents a semantic reprojection framework for map-relative nighttime UAV localization by aligning segmented thermal observations with a globally referenced, semantically labeled 3D map constructed from daytime RGB data. Rather than relying on appearance-based correspondence, localization is formulated in a shared semantic domain and solved via a symmetric bidirectional reprojection objective with confusion-aware weighting to improve robustness under segmentation uncertainty. The approach is evaluated offline across 6.5 km of nighttime, real-world UAV flight trajectories in urban and semi-structured environments. Relative to RTK GNSS ground truth, the system achieves a bias-corrected RMSE2D of 2.18 m and a median RMSE2D of 1.52 m. Results show that localization performance is strongly correlated with the availability of semantic edge evidence and that large-error events are spatially localized to semantically ambiguous areas rather than uniformly distributed. These findings indicate that semantic reprojection offers a promising pathway toward globally referenced nighttime UAV localization using thermal imagery alone.

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