The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm

Dwijayanti, Suci (2021) The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, 7 (2). pp. 193-206. ISSN 23383070

[thumbnail of jiteki 1.pdf] Text
jiteki 1.pdf - Published Version

Download (1MB)

Abstract

The challenge with using the Unmanned Aerial Vehicle (UAV) is when the UAV makes a landing. This problem can be overcome by developing a landing vision through helipad detection. This helipad detection can make it easier for UAVs to land accurately and precisely by detecting the helipad using a camera. Furthermore, image processing technology is used on the image produced by the camera. You Only Look Once (YOLO) is an image processing algorithm developed to detect objects in real-time. It results from the development of one of the Convolutional Neural Network (CNN) algorithm methods. Therefore, in this study, the YOLO method was used to detect a helipad in real-time. The models used in the YOLO algorithm were Mean-Shift and Tiny YOLO VOC. The Tiny YOLO VOC model performed better than the Mean-Shift method in detecting helipads. The test results obtained a confidence value of 91.1%, and the system processing speed reached 35 frames per second (fps) in bright conditions and 37 fps in dark conditions at an altitude of up to 20 meters.

Item Type: Article
Subjects: #3 Repository of Lecturer Academic Credit Systems (TPAK) > Articles Access for TPAK (Not Open Sources)
Divisions: 03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User: Ms Suci Dwijayanti
Date Deposited: 25 May 2023 00:27
Last Modified: 25 May 2023 00:27
URI: http://repository.unsri.ac.id/id/eprint/105017

Actions (login required)

View Item View Item