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

Authors

  • Bhakti Yudho Suprapto Universitas Sriwijaya
  • A. Wahyudin Universitas Sriwijaya
  • Hera Hikmarika
  • Suci Dwijayanti Universitas Sriwijaya

DOI:

https://doi.org/10.26555/jiteki.v7i2.20684

Keywords:

Object Detection, Helipad, Image Processing, Unmanned Aerial Vehicle (UAV), YOLO Algorithm

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, and it is the result of 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.

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Published

2021-06-05

How to Cite

Suprapto, B. Y., Wahyudin, A., Hikmarika, H., & Dwijayanti, S. (2021). The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 7(2), 193–206. https://doi.org/10.26555/jiteki.v7i2.20684

Issue

Vol. 7 No. 2 (2021): August

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