Skip to main content
Log in

Architecture of Software for Simulating Drone Operation

  • Published:
Russian Engineering Research Aims and scope

Abstract

A typical scenario for the use of a drone group is considered. In this scenario, based on programmed control, each vehicle in the group moves along a specified trajectory determined in preflight planning, in which the target distribution is selected on the basis of the coordinates of the targets, the coordinates of the points of drone deployment, and the coordinates of the no-fly zones. Software architecture for simulation of the drone systems in group scenarios is proposed. The architecture is based on selecting two components of the software: software for the ground control module; and software for the drones. The set of modules and algorithms within each component is considered.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.

Similar content being viewed by others

REFERENCES

  1. GOST (State Standard) R 56122–2014: Air Transport. Unmanned Aircraft Systems. General Requirements, Moscow: Standartinform, 2020.

  2. Kalyaev, I.A., Gaiduk, A.R., and Kapustyan, S.G., Modeli i algoritmy kollektivnogo upravleniya v gruppakh robotov (Models and Algorithms of Collective Control in Groups of Robots), Moscow: Fizmatlit, 2009.

  3. Merkulov, V.I., Kanashchenkov, A.I., Chernov, V.S., et al., Aviatsionnye sistemy radioupravleniya. Tom 3. Sistemy komandnogo radioupravleniya. Avtonomnye i kombinirovannye sistemy navedeniya (Aviation Radio Control Systems, Vol. 3: Command Radio Control Systems. Autonomous and Combined Navigation Systems), Moscow: Radiotekhnika, 2004.

  4. Puterman, M., Markov Decision Processes: Discrete Stochastic Dynamic Programming, New York: Wiley, 2005.

    MATH  Google Scholar 

  5. Murphy, R.A., An approximate algorithm for a weapon target assignment stochastic program, in Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems, Dordrecht: Kluwer, 2000, pp. 406–421,

    Google Scholar 

  6. Abramov, L.M. and Kapustyan, V.F., Matematicheskoe programmirovanie. Uchebnoe posobie (Manual on Mathematical Programming), Leningrad: Leningr. Gos. Univ., 1981.

  7. Gass, S.I., Linear Programming: Methods and Applications, New York: McGraw-Hill, 1958.

    MATH  Google Scholar 

  8. Modi, P., Shen, W., Tambe, M., and Yokoo, M., An asynchronous complete method for general distributed constraint optimization. https://www.researchgate.net/publication/2588263_An_Asynchronous_ Complete_Method_for_General_Distributed_Constraint_Optimization. Cited April 15, 2021.

  9. Yokoo, M. and Hirayaman, K., Algorithms for distributed constraint satisfaction: a review, Auton. Agents Multi-Agent Syst., 2000, vol. 3, no. 2, pp. 198–212.

    Article  Google Scholar 

  10. Rasmussen, S., Chandler, P., and Schumacher, C., Investigation of single vs. multiple task tour assignments for UAV cooperative control, Proc. AIAA Guidance, Navigation, and Control Conf., Monterey, CA, 2002.

  11. Nemhauser, G. and Wolsey, B., Integer and Combinatorial Optimization, New York: Wiley, 1999.

    MATH  Google Scholar 

  12. Bertsekas, D. and Castanon, D., Parallel primal-dual methods for the minimum cost flow problem, Comput. Optim. Appl., 1993, vol. 2, pp. 319–338.

    MathSciNet  MATH  Google Scholar 

  13. Bertsekas, D., Auction algorithms for network flow problems: a tutorial Introduction, Comput. Optim. Appl., 1992, vol. 1, pp. 7–66.

    Article  MathSciNet  Google Scholar 

  14. MAVLink Developer Guide. https://mavlink.io/en/. Cited April 15, 2021.

  15. ArduPilot. https://ardupilot.org/ardupilot/. Cited April 15, 2021.

  16. Larman, C., Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and the Unified Process, Upper Saddle River, NJ: Prentice Hall, 2001.

    Google Scholar 

  17. DRONEKIT: Developer tools for drones. https://dronekit.io/. Cited April 15, 2021.

  18. Pymavlink 2.4.17. https://pypi.org/project/pymavlink/. Cited April 15, 2021.

  19. tkinter: Python interface to Tcl/Tk. https://docs.python.org/3/library/tkinter.html. Cited April 15, 2021.

  20. Matplotlib: visualization with Python. https://matplotlib.org/. Cited April 15, 2021.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. N. Evdokimenkov.

Additional information

Translated by B. Gilbert

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Evdokimenkov, V.N., Kim, R.V. & Popov, S.S. Architecture of Software for Simulating Drone Operation. Russ. Engin. Res. 41, 1209–1212 (2021). https://doi.org/10.3103/S1068798X21120121

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S1068798X21120121

Keywords:

Navigation