Vision based localization of drones with a DSM

Timothy Krock; Jaired Collins; Joshua Fraser; Hadi AliAkbarpour; Ricky Massaro; Guna Seetharaman; Kannappan Palaniappan

doi:10.1117/12.3029750

10 June 2024 Vision based localization of drones with a DSM

Timothy Krock, Jaired Collins, Joshua Fraser, Hadi AliAkbarpour, Ricky Massaro, Guna Seetharaman, Kannappan Palaniappan

Proceedings Volume PC13037, Geospatial Informatics XIV; PC1303708 (2024) https://doi.org/10.1117/12.3029750
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

We explore an approach for vision-based GPS denied navigation of drones. We find SuperPoint/Superglue feature correspondences between two coplanar images: the drone image on the ground, and a satellite view of the flight area. The drone image is projected onto the ground using non-GPS data available to the drone, namely the compass and the barometer. Features on the drone image are projected back to the drone camera plane. Features on the satellite image are projected into 3D using a digital elevation map. The correspondences are then used to estimate the drone’s position. Drone coordinate estimates are evaluated against drone GPS metadata.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Timothy Krock, Jaired Collins, Joshua Fraser, Hadi AliAkbarpour, Ricky Massaro, Guna Seetharaman, and Kannappan Palaniappan "Vision based localization of drones with a DSM", Proc. SPIE PC13037, Geospatial Informatics XIV, PC1303708 (10 June 2024); https://doi.org/10.1117/12.3029750

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