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Conference Papers Year : 2022

Automated Foreign Object Debris Detection System based on UAV


The presence of Foreign Object Debris (FOD) on airport platforms constitutes a big risk, both for aircraft and for personnel. This debris, whatever its nature or size, whether it's a private effect, a tool, a component from an aircraft, or any object, As soon because it isn't observed and removed, it's liable becoming a FOD within the moving area. FOD can even be violently projected by jet blast, which might cause damage to other aircraft and injure personnel on the bottom, This paper discuss briefly FOD detection systems and the use of unmanned aerial systems for an automated FOD detection system on runways, which involves taking images of the runway with an Unmanned Aerial Vehicle (UAV), which could be detected and identified using artificial intelligence techniques. The method for determining an exact FOD position from aerial data is described in this study using a perspective projection transformation is used to determine the object's location in the field. For accurate findings, a strong object detection is essential, which is why the cutting-edge deep neural network YOLOV5 is used with both DeepSort Object tracking method. The paper represent an Automated UAV Navigation with PID control based for path tracking. A GUI that has been developed alow the operator to select the runway's intended path to be scanned and visualize the tracked FOD that has been found and its position in order to send a report that the operator can erase from the runway. The proposed system was assessed in real-time testing and a built-in Simulation under GAZEBO using the commercial quad copter Bebop connected to a base station operating under the Robot Operating System (ROS). our approach successfully identified several FODs using a combination of YOLOv5 and deepsort with an inference speed of 30 fps with a high accuarcy over 80%. The advantages of this system is the fulfilment of the FAA performance criteria of an AFDS, it facilitate the FOD scanning operation by using a graphical user...
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Dates and versions

hal-03968566 , version 1 (01-02-2023)



Chadi M'Sila, Redouane Ayad, Naïma Aït Oufroukh. Automated Foreign Object Debris Detection System based on UAV. IEEE International Conference on Networking, Sensing and Control (ICNSC 2022), Dec 2022, Shanghai, China. pp.1-7, ⟨10.1109/ICNSC55942.2022.10004050⟩. ⟨hal-03968566⟩
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