Article
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Preserved in Portico This version is not peer-reviewed
SiaN-VO: Siamese Network for Visual Odometry
Version 1
: Received: 4 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (07:18:56 CET)
A peer-reviewed article of this Preprint also exists.
Faiçal, B.S.; Marcondes, C.A.C.; Verri, F.A.N. SiaN-VO: Siamese Network for Visual Odometry. Sensors 2024, 24, 973. Faiçal, B.S.; Marcondes, C.A.C.; Verri, F.A.N. SiaN-VO: Siamese Network for Visual Odometry. Sensors 2024, 24, 973.
Abstract
Despite advances in the reliability of sensory devices used by drones, the integrity of information from some devices is still considered an obstacle to ensuring successful flight plans. It is widely known that GNSS can suffer attacks or lose the signal from satellites, which can cause the drone to fail to complete its flight plan. In this context, we propose SiaN-VO, a Siamese network for visual odometry prediction. In our initial studies, this approach proved satisfactory for flights in static conditions (speed and height). Although interesting, these conditions do not reflect real flight conditions. In this sense, we have advanced our studies to propose the SiaN-VO, which fuses data from different sensors to enable displacement predictions to be made in dynamic flight conditions.
Keywords
Visual Odometry; Drone; autonomous flight
Subject
Engineering, Other
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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