Russian Federation
UDC 621.398
UDC 004.896
The article describes a subsystem of acoustic localization of a decentralized swarm of unmanned aerial vehicles (UAVs) operating independently of satellite navigation systems. The proposed method uses the acoustic signal arrival time difference, estimated using generalized phase transformation cross‑correlation. The resulting time delays are transformed into hyperbolic constraints, which are solved by the nonlinear least squares (Trust‑Region Reflective) method with a soft L1 loss. Experiments in flight conditions show an average localization error of less than 3 meters in a two-dimensional plane and wind resistance of up to 8 m/s (error <2.2 m). The subsystem is integrated with a delay monitoring mechanism between C++ and Python, which allows for automatic switching to a simplified algorithm with three nearby sensors when the roundabout time is >280 ms. The presented architecture has proven its suitability for swarms operating in conditions of GPS jamming, smoke or urban "canyons".
acoustic localization, drone swarm, navigation without GPS, nonlinear least squares method, Trust‑Region Reflective
1. Floreano D., Husbands P., Nolfi S. Evolutionary robotics // Springer Handbook of Robotics. – Berlin, Heidelberg: Springer, 2008. – Pp. 1423-1451. DOI: https://doi.org/10.1007/978-3-540-30301-5_62
2. Van den Berg J., Lin M., Manocha D. Reciprocal velocity obstacles for real-time multi-agent navigation // 2008 IEEE International Conference on Robotics and Automation. – 2008. – Pp. 1928-1935. DOI: https://doi.org/10.1109/ROBOT.2008.4543489
3. Zarevich A. I., Makarenko F. V., Yagodkin A. S., Zol'nikov K. V. Modelirovanie povedeniya mobil'nyh robotov s ispol'zovaniem geneticheskih algoritmov // Modelirovanie sistem i processov. – 2022. – T. 15, № 3. – S. 7-16. DOI: https://doi.org/10.12737/2219-0767-2022-15-3-7-16
4. Karaman S., Frazzoli E. Sampling-based algorithms for optimal motion planning // The International Journal of Robotics Research. – 2011. – Vol. 30, № 7. – Pp. 846-894. DOI: https://doi.org/10.1177/0278364911406761
5. Santos F. M., Silva M. G., Moreira A. P. Hybrid RRT*-RVO for multi-robot navigation in dynamic environments // ROBOTICA. – 2019. – Vol. 37, № 9. – Pp. 1571-1587.
6. Modelirovanie oslableniya ioniziruyuschego izlucheniya za schet zaschitnogo korpusa mikroshem / A. V. Poluektov, R. Yu. Medvedev, A. I. Zarevich // Modelirovanie sistem i processov. – 2024. – T. 17, № 2. – S. 93–100. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-2-93-100. – EDN QQRQXE.
7. Regressionnyy analiz ocenki zagruzki platnogo otdeleniya stomatologicheskoy polikliniki / T. P. Novikova, A. A. Bodin, A. I. Zarevich // Nauchno-tehnicheskiy vestnik Povolzh'ya. – 2023. – № 3. – S. 77–80.
8. Primenenie elementov otricatel'noy logiki pri postroenii energoeffektivnogo kombinacionnogo ustroystva / F. V. Makarenko, A. S. Yagodkin, O. A. Denisova [i dr.] // Modelirovanie sistem i processov. – 2023. – T. 16, № 1. – S. 56–66. – DOIhttps://doi.org/10.12737/2219-0767-2023-16-1-56-66.
9. Tehnologiya razrabotki RTL-modeli opisaniya izdeliya pri razrabotke programmno-analiticheskogo kompleksa SAPR / D. V. Shehovcov, A. M. Plotnikov, K. V. Zol'nikov, A. I. Zarevich // Modelirovanie sistem i processov. – 2023. – T. 16, № 3. – S. 79–86. DOI: https://doi.org/10.12737/2219-0767-2023-16-3-79-86
10. Geneticheskie algoritmy v modelirovanii povedeniya robota / A. S. Logvinenko, L. Yu. Smilyanskiy, A. I. Zarevich, F. V. Makarenko // Novye aspekty modelirovaniya sistem i processov : materialy Mezhdunar. nauch.-prakt. konf. / otv. red. V. K. Zol'nikov, A. I. Zarevich. – Voronezh, 2023. – S. 94–103.
11. Komp'yuternoe modelirovanie raboty tranzistorov i poluprovodnikovyh priborov na ego osnove / A. V. Poluektov, F. V. Makarenko, R. Yu. Medvedev // Modelirovanie sistem i processov. – 2023. – T. 16, № 1. – S. 77–84. – DOIhttps://doi.org/10.12737/2219-0767-2023-16-1-77-84. – EDN LOLZMT.
12. Modelirovanie raboty dioda i ocenka parametrov ego raboty / A. V. Poluektov, R. Yu. Medvedev, V. K. Zol'nikov // Modelirovanie sistem i processov. – 2023. – T. 16, № 1. – S. 85–93. – DOIhttps://doi.org/10.12737/2219-0767-2023-16-1-85-93. – EDN RALIJG.
13. Integraciya programmnogo produkta Calibre v sredu Cadence Virtuoso i povyshenie intellektual'nyh svoystv SAPR proektirovanii mikroshem / A. V. Poluektov, D. V. Shehovcov, I. V. Skorkin, P. A. Chubunov // Modelirovanie sistem i processov. – 2023. – T. 16, № 4. – S. 71–80. – DOIhttps://doi.org/10.12737/2219-0767-2023-16-4-71-80. – EDN PBUJZO.
14. Ispol'zovanie storonnih bibliotek pri napisanii programm dlya obrabotki statisticheskih dannyh / A. V. Poluektov, F. V. Makarenko, A. S. Yagodkin // Modelirovanie sistem i processov. – 2022. – T. 15, № 2. – S. 33–41. – DOIhttps://doi.org/10.12737/2219-0767-2022-15-2-33-41. – EDN HHYURU.
15. Eksperimental'nye issledovaniya radiacionnogo vozdeystviya na mikroshemy FRAM / V. K. Zol'nikov, N. G. Gamzatov, V. I. Anciferova [i dr.] // Modelirovanie sistem i processov. – 2022. – T. 15, № 3. – S. 16–24. – DOIhttps://doi.org/10.12737/2219-0767-2022-15-3-16-24. – EDN UOCKEW.
16. Modelirovanie kolebatel'nyh processov v pakete MVSTUDIUM / A. V. Poluektov, K. V. Zol'nikov, V. I. Anciferova // Modelirovanie sistem i processov. – 2021. – T. 14, № 4. – S. 139–148. – DOIhttps://doi.org/10.12737/2219-0767-2021-14-4-139-148. – EDN PPOUDI.
17. Apparatno-programmnyy kompleks dlya avtomatizirovannyh ispytaniy sil'notochnyh preobrazovateley / A. I. Zarevich, S. V. Murav'ev, E. V. Bedareva [i dr.] // Izvestiya Tomskogo politehnicheskogo universiteta. – 2013. – T. 322, № 4. – S. 180–184.
