ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)

vol 63 / September, 2020

DOI 10.17586/0021-3454-2017-60-12-1124-1129

UDC 621. 391


A. B. Bushuev
ITMO University, Department of Control Systems and Informatics; Associate Professor

Y. V. Litvinov
ITMO University, Saint Petersburg, 197101, Russian Federation; Senior lecturer

G. M. Shmyhelskiy
ITMO University, Saint Petersburg, 197101, Russian Federation; postgraduate

E. G. Shchaev
ITMO University, Department of Control Systems and Informatics; Student

A. I. Tyurin
ITMO University, Department of Computer Science and Control Systems; Student

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Abstract. The control system of an unmanned aerial vehicle (UAV) such as a quadrocopter is considered that allows solving problems of identification of a mobile object and tracking it when driving on a predetermined route in an emergency. For recognition of objects, the system uses sensors built into the quadrocopter and an on-board video camera as the basis of technical vision. An algorithm for identifying the object on the image obtained from the front camera of the ArDrone quadrocopter is proposed. Based on the analysis performed, the Viola-Jones method is used in the further work; it exploits the principle of contrasting sections of the shape depending on the object. The use of the proposed algorithm allows to ensure the movement of the UAV along a given trajectory, to search for a given object and, if detected, to monitor it or send information to the base.  
Keywords: quadrocopter, trajectory control, UAVs, tracking, mobile unit, machine vision, rescue operations

  1. Buy V.Sh., Bushuev A.B., Shmigel'skiy G.M., Litvinov Yu.V., Shchaev E.G. Journal of Instrument Engineering, 2015, no. 8(58), pp. 593–599 (in Russ.)
  2. Viola P., Jones M.J. International Journal of Computer Vision, 2004, no. 2(57), pp. 137–154.
  3. Viola P., Jones M.J. IEEE Conf. on Computer Vision and Pattern Recognition, Kauai, Hawaii, USA, 2001, no. 1, pp. 511–518.
  4. Russ.)
  5. Lienhart R., Kuranov А., Pisarevsky V. Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, 2003, no. 2781.
  7. 208092. (in Russ.)
  8. Hidayatullah P., Konik H. International Conference on Electrical Engineering and Informatics, ICEEI 2011, Bandung, Indonesia, IEEE, 2011, рp. 143–148.
  9. Jolliffe I.T. Principal Component Analysis, Springer, NY, 2002, 487 p.
  10. Gikhman I.I., Skorokhod A.V. Vvedenie v teoriyu sluchaynykh protsessov (Introduction to the Theory of Random Processes), Moscow, 1965, 570 р. (in Russ.)
  11. Puchinin S.A. Intellekt. Sist. Proizv. (Intelligent Systems in Manufacturing), 2009, no. 13(1), pp. 106–110. (in Russ.)
  12. Piskorski S., Brulez N., Pierre E. AR.Drone Developer Guide, 2011, 107 р.
  13. Endres T., Hobley S., Vinel J. ArDrone Control .NET – An application for flying the Parrot AR drone in Windows, 2011,
  14. Bradsky G., Kaehler A. Learning OpenCV, O’Reilly, 2008, 580 p.
  15. Lur'e A.I. Analiticheskaya mekhanika (Analytical Mechanics), Moscow, 1961, 824 р. (in Russ.)