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Visual drone detection and tracking for autonomous operation from maritime vessel
Halleux, T.; Nguyen, T.-T.; Hamesse, C.; De Cubber, G.; Janssens, B. (2022). Visual drone detection and tracking for autonomous operation from maritime vessel, in: 2022 International Symposium on Measurement and Control in Robotics (ISMCR). pp. 59-65. https://dx.doi.org/10.1109/ISMCR56534.2022.9950568
In: (2022). 2022 International Symposium on Measurement and Control in Robotics (ISMCR). IEEE: United States. ISBN 978-1-6654-5497-1; e-ISBN 978-1-6654-5496-4. [diff. pag.] pp. https://dx.doi.org/10.1109/ISMCR56534.2022, meer
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Documenttype: Congresbijdrage
Trefwoord
    Marien/Kust
Author keywords
    Object Detection; Tracking; UA V; synthetic data
Auteurs  Top 
  • De Cubber, G., meer
  • Janssens, B., meer
Abstract
    To allow incorporation of autonomous Unmanned Aerial Vehicles (UAV's/drones) into maritime military operations, it is critical to be able to accurately localize the UAV with respect to the moving maritime vessel during the take-off and landing phases. This work addresses the study and implementation of a visual detection, tracking and three-dimensional positioning method for a specific drone from a moving maritime vessel. The YOLOv5 detector and the OceanPlus tracker have been trained on a custom dataset with good performance in accuracy and processing time. The drone's position with respect to the vessel is estimated by applying stereo triangulation to the centres of the bounding boxes returned by the object detectors and trackers. The performance of the proposed positioning method was evaluated in a realistic simulated environment in the Unreal Game Engine. The proposed method allows detection, tracking, and positioning of a target drone at ranges exceeding 100m while achieving positioning errors below 10cm during landing phases.
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