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Küresel Seyrüsefer Uydu Sistemleri Kullanılamayan Alanlarda İnsansız Hava Aracının Stabilizasyonunun Artırılması

Year 2021, Volume: 5 Issue: 1, 36 - 44, 30.06.2021
https://doi.org/10.30518/jav.932978

Abstract

Günümüzde kullanılan insansız hava araçlarının (İHA) neredeyse tamamı, küresel seyrüsefer uydu sistemini (Global Navigation Setallite System, GNSS) kullanmaktadır. Bu sistem, hava aracına yüksek hassasiyetli konum, hız ve zaman bilgisi sağlamaktadır. Ancak GNSS kullanıldığında, yüksek yapıların arasında, engebeli arazilerin bazı bölgelerinde ve kapalı alanlarda veri akışında aksaklıklar meydana gelmektedir. Bu sistemin eksikliğinde, ataletsel ölçüm birimi (Inertial Measurement Unit, IMU) içerisinde bulunan jiroskop, ivmeölçer ve manyetometre verileri kullanılmaktadır. Kapalı ortamda uçuş yapılırken, harici bir seyrüsefer sistemi kullanılamadığı zaman, IMU’ da sapmalar meydana gelmekte ve bu sapmalar, düzeltilememekte, uçuş boyunca da artarak devam etmektedir. Bu çalışmada, kapalı ortam uçuşlarında ortaya çıkan sapmaları azaltmak ve buna bağlı olarak uçuş stabilitesini artırmak için optik akış, kızılötesi ve ultrasonik sensörlerin birlikte kullanıldığı bir İHA modeli sunulmuştur. Geliştirilen İHA’ nın uçuş stabilitesini karşılaştırma açısından kapalı ortam uçuşu için iki farklı konfigürasyon kullanılmıştır. Arduino üzerinde geliştirilen algoritmalar sayesinde, İHA’ nın kapalı alanda engellerden kaçınması sağlanmış ve hem IMU’ daki sapmalar azaltılmış hem de uçuş stabilizasyonu artırılmıştır.

Supporting Institution

Erciyes Üniversitesi

Project Number

FYL-2019-8951

Thanks

Bu çalışma Erciyes Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi tarafından FYL-2019-8951 nolu proje kapsamında desteklenmiştir.

References

  • S. Akyürek, M. A. Yılmaz, M. Taşkıran, İnsansız hava araçları: Muharebe alanında ve terörle mücadelede devrimsel dönüşüm. Türkiye: Bilgesam Yayınları, İstanbul, 2012.
  • M. Konar, “Redesign of morphing UAV's winglet using DS algorithm based ANFIS mode,” Aircraft Engineering and Aerospace Technology, 1214-1222, 2019.
  • M. Konar, E. T. Kekeç, “İnsansız Hava Araçlarının Uçuş Süresinin Termal Hava Akımları Kullanılarak Arttırımı,” Avrupa Bilim ve Teknoloji Dergisi, (23), 394-400, 2021.
  • G. Balamurugan, J. Valarmathi, V.P.S. Naidu, “Survey on UAV Navigation in GPS Denied Environments,” International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, India, 2016, ss. 198-204.
  • M. Konar, A. Turkmen, T. Oktay, “Improvement of the thrust-torque ratio of an unmanned helicopter by using the ABC algorithm,” Aircraft Engineering and Aerospace Technology,1133-1139, 2020.
  • G. Mao, S. Drake, B.D.O. Anderson, “Design of an Extended Kalman Filter for UAV Localization,” IEEE Information, Decision and Control (IDC), Adelaide, Australia, 2007, ss. 224-229.
  • S. Lange, N. Sunderhauf, P. Protzel, “A Vision Based Onboard Approach for Landing and Position Control of An Autonomous Multirotor UAV in GPS-Denied Environments,” International Conference on Advanced Robotics, Munich, Germany, 2009, ss. 1-6.
  • C. Schlaile, O. Meister, N. Frietsch, C. Keßler, J. Wendel, G.F. Trommer, “Using Natural Features for Vision Based Navigation of An Indoor-VTOL MAV,” Aerospace Science and Technology, 13 (7), 349–357, 2009.
  • C. Shen, Z. Bai, H. Cao, K. Xu, C. Wang, H. Zhang, D. Wang, J. Tang, J. Liu, “Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment,” Hindawi Publishing Corporation Journal of Sensors, 1-10, 2016.
  • J. Langelaan, S. Rock, “Passive GPS-Free Navigation for Small UAVs,” IEEE Aerospace Conference, Big Sky, USA, 2005, ss. 1-9.
  • R. Mebarki, V. Lippiello, B. Siciliano, “Nonlinear Visual Control of Unmanned Aerial Vehicles in GPS-Denied Environments,” The Institute of Electrical and Electronics Engineers, 31(4), 1004-1007, 2015.
  • S. Carnduff, “System identification of unmanned aerial vehicles,” Cranfield University, Doctorate Thesis, United Kingdom, 2008.
  • S. C. Quebe, “Modeling, parameter estimation and navigation of indoor quadrotor robots,” Brigham Young University, Master Thesis, United States of America, 2013.
  • R. Mebarki, J. Cacace, V. Lippiello, “Velocity Estimation of an UAV Using Visual and IMU Data in a GPS-Denied Environment,” IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Linkoping, Sweden, 2013, ss. 1-6.
  • S. P. H. Driessen, N. H. J. Janssen, L. Wang, J. L Palmer, H. Nijmeijer, “Experimentally Validated Extended Kalman Filter for UAV State Estimation Using Low-Cost Sensors,” 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018, ss. 43-48.
  • T. Bresciani, “Modelling, identification and control of a quadrotor helicopter,” Lund University, Master thesis, Sweden, 2008.
  • Z. Benić, P. Piljek, D. Kotarski, “Mathematical Modelling of Unmanned Aerial Vehicles with Four Rotors,” Interdisciplinary Description of Complex Systems: INDECS, 14(1), 88-100, 2016.
  • M. S. Gençağ, “Kapalı ortamlarda insansız hava aracının stabilizasyonunun iyileştirilmesi,” Erciyes Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Kayseri, Türkiye, 2020.

Increasing the Stabilization of Unmanned Aerial Vehicle in Global Navigation Satellite System Unavailable Areas

Year 2021, Volume: 5 Issue: 1, 36 - 44, 30.06.2021
https://doi.org/10.30518/jav.932978

Abstract

Nowadays nearly all of unmanned aerial vehicles (UAV) use Global Navigation Setallite System (GNSS). This system provides high-precision position, speed and time information to the aircraft. However, some problems can occour about data flow between high buildings, in some areas of rough terrain and indoor environment when GNSS is used. If this system is not available, the gyroscope, accelerometer and magnetometer data contained in the Inertial Measurement Unit (IMU) are used. Indoor flight, when an external navigation system cannot be used, deviations occur in the IMU. These deviations cannot be corrected and continue to increase throughout the flight. In this study, an UAV, in which optical flow, infrared and ultrasonic sensors are used together, has been presented to reduce the deviations that occur in indoor flights and increase flight stability accordingly. Two different configurations were used for indoor flight in terms of comparing the flight stability of the developed UAV. Thanks to the algorithms developed on Arduino, the UAV has been allowed to avoid obstacles in the closed area, and both the deviations in the IMU have been reduced and the flight stabilization has been increased. 

Project Number

FYL-2019-8951

References

  • S. Akyürek, M. A. Yılmaz, M. Taşkıran, İnsansız hava araçları: Muharebe alanında ve terörle mücadelede devrimsel dönüşüm. Türkiye: Bilgesam Yayınları, İstanbul, 2012.
  • M. Konar, “Redesign of morphing UAV's winglet using DS algorithm based ANFIS mode,” Aircraft Engineering and Aerospace Technology, 1214-1222, 2019.
  • M. Konar, E. T. Kekeç, “İnsansız Hava Araçlarının Uçuş Süresinin Termal Hava Akımları Kullanılarak Arttırımı,” Avrupa Bilim ve Teknoloji Dergisi, (23), 394-400, 2021.
  • G. Balamurugan, J. Valarmathi, V.P.S. Naidu, “Survey on UAV Navigation in GPS Denied Environments,” International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, India, 2016, ss. 198-204.
  • M. Konar, A. Turkmen, T. Oktay, “Improvement of the thrust-torque ratio of an unmanned helicopter by using the ABC algorithm,” Aircraft Engineering and Aerospace Technology,1133-1139, 2020.
  • G. Mao, S. Drake, B.D.O. Anderson, “Design of an Extended Kalman Filter for UAV Localization,” IEEE Information, Decision and Control (IDC), Adelaide, Australia, 2007, ss. 224-229.
  • S. Lange, N. Sunderhauf, P. Protzel, “A Vision Based Onboard Approach for Landing and Position Control of An Autonomous Multirotor UAV in GPS-Denied Environments,” International Conference on Advanced Robotics, Munich, Germany, 2009, ss. 1-6.
  • C. Schlaile, O. Meister, N. Frietsch, C. Keßler, J. Wendel, G.F. Trommer, “Using Natural Features for Vision Based Navigation of An Indoor-VTOL MAV,” Aerospace Science and Technology, 13 (7), 349–357, 2009.
  • C. Shen, Z. Bai, H. Cao, K. Xu, C. Wang, H. Zhang, D. Wang, J. Tang, J. Liu, “Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment,” Hindawi Publishing Corporation Journal of Sensors, 1-10, 2016.
  • J. Langelaan, S. Rock, “Passive GPS-Free Navigation for Small UAVs,” IEEE Aerospace Conference, Big Sky, USA, 2005, ss. 1-9.
  • R. Mebarki, V. Lippiello, B. Siciliano, “Nonlinear Visual Control of Unmanned Aerial Vehicles in GPS-Denied Environments,” The Institute of Electrical and Electronics Engineers, 31(4), 1004-1007, 2015.
  • S. Carnduff, “System identification of unmanned aerial vehicles,” Cranfield University, Doctorate Thesis, United Kingdom, 2008.
  • S. C. Quebe, “Modeling, parameter estimation and navigation of indoor quadrotor robots,” Brigham Young University, Master Thesis, United States of America, 2013.
  • R. Mebarki, J. Cacace, V. Lippiello, “Velocity Estimation of an UAV Using Visual and IMU Data in a GPS-Denied Environment,” IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Linkoping, Sweden, 2013, ss. 1-6.
  • S. P. H. Driessen, N. H. J. Janssen, L. Wang, J. L Palmer, H. Nijmeijer, “Experimentally Validated Extended Kalman Filter for UAV State Estimation Using Low-Cost Sensors,” 18th IFAC Symposium on System Identification (SYSID 2018), Stockholm, Sweden, 2018, ss. 43-48.
  • T. Bresciani, “Modelling, identification and control of a quadrotor helicopter,” Lund University, Master thesis, Sweden, 2008.
  • Z. Benić, P. Piljek, D. Kotarski, “Mathematical Modelling of Unmanned Aerial Vehicles with Four Rotors,” Interdisciplinary Description of Complex Systems: INDECS, 14(1), 88-100, 2016.
  • M. S. Gençağ, “Kapalı ortamlarda insansız hava aracının stabilizasyonunun iyileştirilmesi,” Erciyes Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Kayseri, Türkiye, 2020.
There are 18 citations in total.

Details

Primary Language Turkish
Subjects Aerospace Engineering
Journal Section Research Articles
Authors

Fatma Yıldırım Dalkıran 0000-0001-8663-241X

Mustafa Samet Gençağ 0000-0002-3212-1814

Project Number FYL-2019-8951
Publication Date June 30, 2021
Submission Date May 6, 2021
Acceptance Date June 29, 2021
Published in Issue Year 2021 Volume: 5 Issue: 1

Cite

APA Yıldırım Dalkıran, F., & Gençağ, M. S. (2021). Küresel Seyrüsefer Uydu Sistemleri Kullanılamayan Alanlarda İnsansız Hava Aracının Stabilizasyonunun Artırılması. Journal of Aviation, 5(1), 36-44. https://doi.org/10.30518/jav.932978

Journal of Aviation - JAV 


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