Research Article
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AUTONOMOUS GUIDANCE SYSTEM for UAVs with IMAGE PROCESSING TECHNIQUES

Year 2022, Issue: 051, 149 - 159, 31.12.2022

Abstract

In this study, object detection is carried out by the image processing techniques of the images captured by the camera of the UAV in an autonomous flight route. After the desired object is detected, an algorithm is designed to land near this object by autonomous guidance of the UAV. In order to ensure the functioning of the algorithm, a UAV control system including ground station software has been designed. In addition, a deep learning-based human recognition system is tested in the algorithm in order to reduce the risk of accidents that may arise from UAV crashes. Image processing techniques were applied to the images taken by the UAV with the designed system and object detection was achieved successfully. 3 different objects to be detected were determined and the processes were repeated for each object. The deep learning-based human recognition process designed in this study has been tested in terms of recognition accuracy by using different models.

Supporting Institution

TUBITAK

Project Number

TUBITAK 2209-A / 1919B012102370

Thanks

This study was supported within the scope of the TUBITAK 2209-A university students’ research projects support program with the application number 1919B012102370.

References

  • [1] Ilhan, I., (2013), Development of image processing based intelligent control algorithms for quadrotors, Firat University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [2] Akyuz, S., (2013), Quad-rotor unmanned aerial vehicle (Quadrotor) design and simulation with pd and fuzzy controller, Ege University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [3] Aksoy, B., Korucu, K., Çalışkan, Ö., Osmanbey, Ş., and Halis, H. D., (2021), İnsansız Hava Aracı ile Görüntü İşleme ve Yapay Zekâ Teknikleri Kullanılarak Yangın Tespiti: Örnek Bir Uygulama, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 112-122.
  • [4] Kar, Y.E, Basgumus, A. and Namdar, M., (2021), Machine Learning Assisted Autonomous Vehicle Design and Control, IEEE 5th Int. Symposium on Multidisciplinary Studies and Innovative Technologies, 462-466.
  • [5] Kar, Y.E, Basgumus, A. and Namdar, M., (2021), Machine Learning and Image Processing Based Autonomous Vehicle Design, IEEE 29th Signal Processing and Comm. Applications Conf., 1-4.
  • [6] Ceylan, A., (2018), Visual-based object tracking with four-rotor aerial vehicle, Firat University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [7] Soyhan, I., Gurel, S. and Tekin, S.A., (2021), Yapay Zeka Tabanlı Görüntü İşleme Tekniklerinin İnsansız Hava Araçları Üzerinde Uygulamaları, Avrupa Bilim ve Teknoloji Dergisi, 24, 469-473.
  • [8] Ozkan, Z., Bayhan, E., Namdar, M. and Basgumus, A., (2021), Object Detection and Recognition of Unmanned Aerial Vehicles Using Raspberry Pi Platform, IEEE 5th International Symposium on Multidisciplinary Studies and Innovative Technologies, 467-472.
  • [9] Bayhan, E., Ozkan, Z., Namdar, M. and Basgumus, A., (2021), Deep Learning Based Object Detection and Recognition of Unmanned Aerial Vehicles, IEEE 3rd Int. Congress on Human-Computer Interaction, Optimization and Robotic Applications, 1-5.
  • [10] Koc, M., (2020), Derin ogrenme kullanarak iha ile hareketli bir hedefin otonom olarak yakalanmasi, Istanbul Sabahattin Zaim University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [11] Ekmen, M. İ., Aydoğdu, Ö., (2020), İnsansız Hava Araçları İçin Görüntü İşleme Tabanlı Otonom İniş. Avrupa Bilim ve Teknoloji Dergisi, 297-303.
  • [12] Sivritaş Ş, Tekin A. (2022), Autonomous 3D Target Tracking via UAV. Balkan Journal of Electrical and Computer Engineering, 10(1), 1 - 9.
  • [13] Toraman S., (2018), Pedestrian Detection with Deep Learning from Unmanned Aerial Imagery, Journal of Aviation, 2(2), 64-69.
  • [14] Bayhan, E., Deligoz, C.B., Seymen, F., Namdar, M. and Basgumus, A., (2022), Unimpeded Walking with Deep Learning, IEEE 30th Signal Processing and Comm. Applications Conf., 1-4.
  • [15] Arndt, C., (1996), An introduction to systematic sensitivity analysis via Gaussian quadrature, Technical Report.
  • [16] Redmon J. and Farhadi, A., (2018), Yolov3: An incremental improvement, arXiv preprint arXiv:1804.02767.
  • Shopa, P., Sumitha, N. and Patra, P.S.K., (2014), Traffic sign detection and recognition using OpenCV, IEEE Int. Conference on Information Communication and Embedded Systems, 1-6.
Year 2022, Issue: 051, 149 - 159, 31.12.2022

Abstract

Project Number

TUBITAK 2209-A / 1919B012102370

References

  • [1] Ilhan, I., (2013), Development of image processing based intelligent control algorithms for quadrotors, Firat University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [2] Akyuz, S., (2013), Quad-rotor unmanned aerial vehicle (Quadrotor) design and simulation with pd and fuzzy controller, Ege University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [3] Aksoy, B., Korucu, K., Çalışkan, Ö., Osmanbey, Ş., and Halis, H. D., (2021), İnsansız Hava Aracı ile Görüntü İşleme ve Yapay Zekâ Teknikleri Kullanılarak Yangın Tespiti: Örnek Bir Uygulama, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 112-122.
  • [4] Kar, Y.E, Basgumus, A. and Namdar, M., (2021), Machine Learning Assisted Autonomous Vehicle Design and Control, IEEE 5th Int. Symposium on Multidisciplinary Studies and Innovative Technologies, 462-466.
  • [5] Kar, Y.E, Basgumus, A. and Namdar, M., (2021), Machine Learning and Image Processing Based Autonomous Vehicle Design, IEEE 29th Signal Processing and Comm. Applications Conf., 1-4.
  • [6] Ceylan, A., (2018), Visual-based object tracking with four-rotor aerial vehicle, Firat University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [7] Soyhan, I., Gurel, S. and Tekin, S.A., (2021), Yapay Zeka Tabanlı Görüntü İşleme Tekniklerinin İnsansız Hava Araçları Üzerinde Uygulamaları, Avrupa Bilim ve Teknoloji Dergisi, 24, 469-473.
  • [8] Ozkan, Z., Bayhan, E., Namdar, M. and Basgumus, A., (2021), Object Detection and Recognition of Unmanned Aerial Vehicles Using Raspberry Pi Platform, IEEE 5th International Symposium on Multidisciplinary Studies and Innovative Technologies, 467-472.
  • [9] Bayhan, E., Ozkan, Z., Namdar, M. and Basgumus, A., (2021), Deep Learning Based Object Detection and Recognition of Unmanned Aerial Vehicles, IEEE 3rd Int. Congress on Human-Computer Interaction, Optimization and Robotic Applications, 1-5.
  • [10] Koc, M., (2020), Derin ogrenme kullanarak iha ile hareketli bir hedefin otonom olarak yakalanmasi, Istanbul Sabahattin Zaim University, Institute of Nat. and Appl. Sci., MSc. Thesis.
  • [11] Ekmen, M. İ., Aydoğdu, Ö., (2020), İnsansız Hava Araçları İçin Görüntü İşleme Tabanlı Otonom İniş. Avrupa Bilim ve Teknoloji Dergisi, 297-303.
  • [12] Sivritaş Ş, Tekin A. (2022), Autonomous 3D Target Tracking via UAV. Balkan Journal of Electrical and Computer Engineering, 10(1), 1 - 9.
  • [13] Toraman S., (2018), Pedestrian Detection with Deep Learning from Unmanned Aerial Imagery, Journal of Aviation, 2(2), 64-69.
  • [14] Bayhan, E., Deligoz, C.B., Seymen, F., Namdar, M. and Basgumus, A., (2022), Unimpeded Walking with Deep Learning, IEEE 30th Signal Processing and Comm. Applications Conf., 1-4.
  • [15] Arndt, C., (1996), An introduction to systematic sensitivity analysis via Gaussian quadrature, Technical Report.
  • [16] Redmon J. and Farhadi, A., (2018), Yolov3: An incremental improvement, arXiv preprint arXiv:1804.02767.
  • Shopa, P., Sumitha, N. and Patra, P.S.K., (2014), Traffic sign detection and recognition using OpenCV, IEEE Int. Conference on Information Communication and Embedded Systems, 1-6.
There are 17 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Salih Tekin 0000-0003-3281-9822

Murat Gok 0000-0001-7010-2377

Mustafa Namdar 0000-0002-3522-4608

Arif Başgümüş 0000-0002-0611-3220

Project Number TUBITAK 2209-A / 1919B012102370
Publication Date December 31, 2022
Submission Date October 10, 2022
Published in Issue Year 2022 Issue: 051

Cite

IEEE S. Tekin, M. Gok, M. Namdar, and A. Başgümüş, “AUTONOMOUS GUIDANCE SYSTEM for UAVs with IMAGE PROCESSING TECHNIQUES”, JSR-A, no. 051, pp. 149–159, December 2022.