@article{ME9EFD08A,
title = "UAV Automatic Landing System Using Gimbal Camera Angle Control and Object Detection",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2023",
issn = "1226-4717",
doi = "10.7840/kics.2023.48.2.241",
author = "Ho Hyun Kang, Soo Young Shin",
keywords = "UAV (Unmmand Aerial Vehicle), Auto landing, GPS (Global Positioning System), Object Detection, Deep Learning",
abstract = "In this paper, we propose a UAV autonomous landing system using the angle control of a gimbal camera and object detection based on deep learning. It controls the position of the UAV in operation based on the bounding box surrounding the destination landing pad through deep learning-based object detection using the camera mounted on the UAV. In the proposed method, without the need for a separate camera, a gimbal camera, one of the existing UAV mission equipment, is used to control the camera angle to look downward, and a companion computer mounted on the UAV is used to control the UAV. In the proposed method, deep learning-based object detection used Yolo v4 tiny, implemented using ROS for drone control, and measured the distance between the landing point and the landing pad for performance evaluation. proved."
}