Development of a quadcopter control simulator with GPS positioning

Аuthors

Makarov A. S.^*, Vladislav A. Chekanin V. A.^**

Moscow State University of Technology "STANKIN", 1, Vadkovsky lane, Moscow, 127994, Russia

*e-mail: MakarovAlex2002@yandex.ru
**e-mail: vladchekanin@yandex.ru

Abstract

The unmanned aerial vehicle (UAV) market is expanding every year, requiring the involvement of an increasing number of personnel as UAV operators, including quadcopter operators. Alongside this, the popularity of quadcopters is growing among aviation model enthusiasts and amateur videographers. The training of qualified UAV operators is a crucial task for ensuring airspace safety. This article examines approaches to training quadcopter operators and presents arguments in favor of using virtual simulators in the training process. Simulators allow users to acquire initial piloting skills without the risk of damaging property or causing harm to others. As part of this study, an analysis of existing simulators was conducted, including a description of their functional capabilities, advantages, and disadvantages. Information is provided about a developed simulator prototype that includes the possibility of integrating proprietary quadcopter controllers with GPS positioning, the lack (or limitation) of support for which is a significant drawback in existing GPS quadcopter simulators. The prototype supports the DJI RC-N1 controller, one of the most widely used as of late 2024. In addition to basic functionality, the developed prototype features training scenarios in which users can acquire UAV control skills under various emergency and critical situations. The use of such a simulator in training will contribute to improving operator preparation quality, reducing accidents, and minimizing financial risks associated with human error. The presented solution can be useful for both hobbyists and future commercial operators. In the future, the project will be developed by extensively expanding the database of supported controllers, creating new training scenarios, and adding more quadcopter models that take into account their physical characteristics and control features.

Keywords:

unmanned aerial vehicle, quadcopter, quadcopter operator training, simulator

References

1. Abramov M.M. New and Promising Directions for the Use of Unmanned Aerial Vehicles. Izvestiya Tul'skogo gosudarstvennogo universiteta. Tekhnicheskie nauki. 2022. No. 3. P. 227-232. (In Russ.)
2. Ronzhin A.L., Nguen V.V., Solenaya O.Ya. Analysis of the problems of unmanned flying manipulators development and UAV physical interaction with ground objects. Trudy MAI. 2018. No. 98. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=90439
3. Zvonikov V.M., Kulikov S.A. On the Features of Professionally Important Qualities of UAV Operators. Prikladnaya psikhologiya i pedagogika. 2024. No. 1. P. 36-43. (In Russ.). DOI: 10.12737/2500-0543-2024-9-1-36-43
4. Vasil'kin D.P., Lyubskii D.I. Approaches to the Development of Educational Virtual Simulators. V Mezhdunarodnaya nauchno-prakticheskaya konferentsiya «Nauchnye issledovaniya i innovatsii»: sbornik statei. Saratov: Izd-vo Tsifrovaya nauka Publ., 2021. P. 39-43.
5. Knyazev A.S. Features of the use of simulators of multifunctional indicators in the process of personnel training. Trudy MAI. 2023. No. 128. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=171412. DOI: 10.34759/trd-2023-128-23
6. Kornilov V.A., Molodyakov D.S., Sinyavskaya Yu.A. Sistema upravleniya mul'tikopterom. Trudy MAI. 2012. No. 62. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=35543
7. Panteleev A.V., Letova T.A., Pomazueva E.A. An application of global optimization methods to the parametric synthesis of generalized proportional-integral-derivative controller for the flight control problems. Trudy MAI. 2015. No. 79. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=55635
8. Danilin Z.A., Kovalenko A.N. Advantages and Disadvantages of the ELRS Protocol for Use in Unmanned Aerial Vehicles. Materialy XIII Respublikanskoi nauchno-prakticheskoi konferentsii «Obespechenie pogranichnoi bezopasnosti i okhrana gosudarstvennoi granitsy respubliki Belarus': teoriya i praktika». Minsk: Institut pogranichnoi sluzhby Respubliki Belarus' Publ., 2024. P. 33.
9. Shevtsov A.S., Il'yukh M.P. Studying Birds Using a Quadcopter. Russkii ornitologicheskii zhurnal. 2020. No. 1930. P. 2456-2470. (In Russ.)
10. Gogolev A.A. Semi-natural modelling of unmanned aerial vehicles like multicopter. Trudy MAI. 2017. No. 92. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=77238
11. Mikhailyuk M.V., Trushin A.M. Collision Calculation of Parallelepipeds in Dynamics Problems. Trudy nauchno-issledovatel'skogo instituta sistemnykh issledovanii Rossiiskoi akademii nauk. 2012. V. 2, No. 2. P. 51-58. (In Russ.)
12. Matveev S.N., Gallyamova E.KH., Kiselev B.V. On the Statistical Assessment of the Implementation of Educational Mathematical Simulators in Training. Problemy sovremennogo pedagogicheskogo obrazovaniya. 2021. No. 71-1. P. 249-255. (In Russ.)
13. Shalimov A.A. Effective Personnel Training for Achieving an Optimal Project Management Strategy. Vestnik MGTU "Stankin". 2009. No. 4 (8). P. 122-125. (In Russ.)
14. Mikhailova M.V. Social Value as a Basis for Professional Development in a Technological Environment. Vestnik MGTU "Stankin". 2018. No. 3 (46). P.147-150. (In Russ.)
15. Nikulina E.N., Tarasova E.V. Methodology for Assessing the Effectiveness of Modernization of Test Units in Aircraft Manufacturing Enterprises. Vestnik MGTU "Stankin". 2016. No.1 (36). P. 91-95. (In Russ.)
16. Dudorov E.A., Sokhin I.G., Kuritsyn A.A. Simulation Stand for Ergonomic Support of Space Robotic Systems. Vestnik MGTU "Stankin". 2021. No. 1 (56). P. 64-75. (In Russ.)
17. Ivanova N.A., Ryabov S.A., Shvartsburg L.E. Multimedia Training Systems for Ensuring Safety in the Industrial Environment. Vestnik MGTU "Stankin". 2015. No. 4 (35). P. 128-131. (In Russ.)
18. Aliev R.S. Mathematical Model for Assessing the Complexity of Software Development. Vestnik MGTU "Stankin". 2015. No. 2 (33). P. 93-97. (In Russ.)
19. Pozdneev B.M., Sutyagin M.V., Selivantsev O.I. Modeling the Structure and Quality Assessment of E-Learning Processes. Vestnik MGTU "Stankin". 2012. No. 1 (19). P. 60-65. (In Russ.)
20. Nwaogu J.M. et al. Enhancing Drone Operator Competency within the Construction Industry: Assessing Training Needs and Roadmap for Skill Development. Buildings. 2024. V. 14, No. 4. P. 1153. DOI: 10.3390/buildings14041153
21. Somerville A. et al. Use of Simulation for Pre-Training of Drone Pilots. Drones. 2024. V. 8, No. 11. P. 640. DOI: 10.3390/drones8110640
22. Usama A. et al. First Person View Drone-FPV. The International Undergraduate Research Conference. The Military Technical College. 2021. V. 5, No. 5. P. 437-440. DOI: 10.21608/iugrc.2021.246400
23. Mairaj A., Baba A.I., Javaid A.Y. Application specific drone simulators: Recent advances and challengesю. Simulation Modelling Practice and Theory. 2019. V. 94, P. 100-117. DOI: 10.1016/j.simpat.2019.01.004
24. Safir P. PID controller. Its types, working and applications. The Scientific Heritage. 2022. V. 102, P. 55-57. DOI: 10.5281/ZENODO.7409178
25. Yoon Y.H., Yun J. Drone Flight Record Forensic System through DUML Packet Analysis. Journal of the Korea Institute of Information Security & Cryptology. 2024. V. 34, No. 1. P. 103-114. DOI: 10.13089/jkiisc.2024.34.1.103
26. Koubâa A. et al. Micro air vehicle link (MAVlink) in a nutshell: A survey. IEEE Access. 2019. V. 7, P. 87658-87680. DOI: 10.1109/access.2019.2924410
27. Gao M. et al. Weather constraints on global drone flyabilityю. Scientific reports. 2021. V. 11, No. 1. P. 12092. DOI: 10.1038/s41598-021-91325-w

Download