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 Program Systems: 
Theory and Applications
 ISSN 2079-3316
12+ 
Bilingual electronic scientific Electronic scientific journal of the Ailamazyan Program System Institute of the Ailamazyan PSI of PSI of Russian Academy of Science of RAS
Volume 15 (2024) . Issue 2 (61) . Paper No. 2 (449)

Artificial intelligence and machine learning

Research Article
DOIDigital Object Identifier 10.25209/2079-3316-2024-15-2-21-36

Gesture control of small unmanned aerial vehicle flight

Nikolai Sergeevich Abramov1, Vita Viktorovna Sattarova2, Vitaly Petrovich Fralenko3Correspondent author, Mikhail Vyacheslavovich Khachumov4

1,3,4Ailamazyan Program Systems Institute of RAS, Ves'kovo, Russia
2RUDN University, Moscow, Russia
4Federal Research Center "Computer Science and Control" of RAS, Moscow, Russia
4MIREA - Russian Technological University, Moscow, Russia
4Russian state university for the humanities, Moscow, Russia
3 Vitaly Petrovich Fralenko — Correspondent author alarmod@pereslavl.ru

Abstract. The problem of constructing gesture commands for controlling a small unmanned aerial vehicle, such as a quadcopter, is considered. Commands coming from a video camera are identified by a classifier based on a convolutional neural network, and the multimodal control interface equipped with an intelligent solver converts them into control commands for the quadcopter. Neural networks from the Ultralytics neural network library allow selecting targets in a frame in real-time. The commands are sent to a specialized program on a smartphone, developed on the basis of DJI SDK flight simulators, which then sends commands via the remote control channel.

The quality of recognition of developed gesture commands for DJI Phantom 3 standard edition quadcopters is investigated, and a brief guide in the form of operator work scenarios with unmanned vehicles is provided. The prospects of gesture control of several vehicles in extreme conditions have been revealed, considering the complex safety challenges of joint flight and interaction of aircraft in confined space. (In Russian).

Keywords: unmanned aerial vehicle, control, gestures, convolutional neural network, Ultralytics, intelligent interface, recognition

MSC-20202020 Mathematics Subject Classification 68T45; 68T07, 68T40MSC-2020 68-XX: Computer science MSC-2020 68Txx: Artificial intelligence MSC-2020 68T45: Machine vision and scene understanding MSC-2020 68T07: Artificial neural networks and deep learning

Acknowledgments: This work was financially supported by the Russian Science Foundation, project № 21\–71\–10056, https://rscf.ru/project/21-71-10056/

For citation: Nikolai S. Abramov, Vita V. Sattarova, Vitaly P. Fralenko, Mikhail V. Khachumov. Gesture control of small unmanned aerial vehicle flight. Program Systems: Theory and Applications, 2024, 15:2, pp. 21–36. (In Russ.). https://psta.psiras.ru/2024/2_21-36.

Full text of article (PDF): https://psta.psiras.ru/read/psta2024_2_21-36.pdf.

The article was submitted 09.02.2024; approved after reviewing 13.03.2024; accepted for publication 17.03.2024; published online 22.04.2024.

© Abramov N. S., Sattarova V. V., Fralenko V. P., Khachumov M. V.
2024
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