SYSTEM FOR SIMULATION OF OVERCOMING OBSTACLES AND ORGANIZING COMMUNICATIONS IN HAZARDOUS ENVIRONMENTS: STRUCTURE AND EXPERIMENTAL EVALUATION
DOI:
https://doi.org/10.26906/SUNZ.2025.3.128Keywords:
simulation, unmanned aerial vehicles, UAV swarm deployment, hazardous environment, routing, paths, obstacle avoidance, communications, Li-Fi, Panda3D, cyber-physical impactsAbstract
The paper presents a comprehensive simulation system for overcoming obstacles and organizing communications in hazardous environments using UAV swarms. The proposed models of environment, obstacles, dynamic influences, and UAVs enable the reproduction of scenarios in destroyed or hard-to-reach indoor areas, considering static and dynamic objects as well as cyber-physical impacts. The simulator architecture is implemented in Python with the Panda3D engine and integrated with data collection and analysis tools (InfluxDB, Grafana, Docker), providing flexible configuration of parameters and reproduction of diverse scenarios. The paper presents experimental results demonstrating the efficiency of routing algorithms (A*, Greedy BestFirst, etc.) and swarm coordination for deploying a Li-Fi-based communication chain. It is shown that the system serves as a valuable research and training tool for testing algorithms, analyzing swarm reliability, evaluating energy efficiency, and resilience to cyber impacts. Future development perspectives include integration with ROS, extension of the sensor library, and modeling of network-level communication protocols.Downloads
References
1. Methods and Software Tools for Reliable Operation of Flying LiFi Networks in Destruction Conditions / H. Fesenko et al. Sensors. 2024. Vol. 24, no. 17. P. 1–27. URL: https://doi.org/10.3390/s24175707 DOI: https://doi.org/10.3390/s24175707
2. Flying Sensor and Edge Network-Based Advanced Air Mobility Systems: Reliability Analysis and Applications for Urban Monitoring / H. Fesenko et al. Drones. 2023. Vol. 7, no. 7. P. 1–28. URL: https://doi.org/10.3390/drones7070409 DOI: https://doi.org/10.3390/drones7070409
3. A UAV-Swarm-Communication Model Using a Machine-Learning Approach for Search-and-Rescue Applications / H. Khalilet al. Drones. 2022. Vol. 6, no. 12. P. 372(1–21). URL: https://doi.org/10.3390/drones6120372 DOI: https://doi.org/10.3390/drones6120372
4. Emergency Communication Service Solution Based on UAV Swarm / J. Jiang et al. Theoretical and Natural Science. 2023. Vol. 19, no. 1. P. 222–233. URL: https://doi.org/10.54254/2753-8818/19/20230561 DOI: https://doi.org/10.54254/2753-8818/19/20230561
5. Chandran I., Vipin K. Multi-UAV Networks for Disaster Monitoring: Challenges and Opportunities from a Network Perspective. Drone Systems and Applications. 2024. Vol. 1, no. 1. P. 1–28. URL: https://doi.org/10.1139/dsa-2023-0079 DOI: https://doi.org/10.1139/dsa-2023-0079
6. Optimizing Drone Deployment for Cellular Communication Coverage During Crowded Events / C. Boucetta et al. Proc. of IEEE ICC. 2019. P. 1–6. URL: https://doi.org/10.1109/MILCOM47813.2019.9020748 DOI: https://doi.org/10.1109/MILCOM47813.2019.9020748
7. Campion M., Ranganathan P., Faruque S. UAV Swarm Communication and Control Architectures: A Review. Journal of Unmanned Vehicle Systems. 2019. Vol. 7, no. 3. P. 93–106. URL: https://doi.org/10.1139/juvs-2018-0009 DOI: https://doi.org/10.1139/juvs-2018-0009
8. A Review of Flying Ad Hoc Networks: Key Characteristics, Applications, and Wireless Technologies / F. Pasandideh et al. Remote Sensing. 2022. Vol. 14, no. 18. P. 4459(1–28). URL: https://doi.org/10.3390/rs14184459 DOI: https://doi.org/10.3390/rs14184459
9. Oh D., Han J. Smart Search System of Autonomous Flight UAVs for Disaster Rescue. Sensors. 2021. Vol. 21, no. 20. P. 6810. URL: https://doi.org/10.3390/s21206810 DOI: https://doi.org/10.3390/s21206810
10. Energy Efficient UAV-Assisted Emergency Communication with Reliable Connectivity and Collision Avoidance / N. Sharvariet al. arXiv preprint. 2023. P. 13. URL: https://doi.org/10.48550/arXiv.2308.16719
11. Kimura T., Ogura M. Distributed Collaborative 3D-Deployment of UAV Base Stations for On-Demand Coverage. IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, Toronto, ON, Canada, 6–9 July 2020. 2020. URL: https://doi.org/10.1109/infocom41043.2020.9155283 DOI: https://doi.org/10.1109/INFOCOM41043.2020.9155283
12. Gadre D., Immanuel J. Utilizing Drones to Restore and Maintain Radio Communication in Disaster Scenarios. Wilderness & Environmental Medicine. 2022. Vol. 33, no. 2. P. 238–244. URL: https://doi.org/10.1016/j.wem.2021.11.007 DOI: https://doi.org/10.1016/j.wem.2021.11.007
13. Kumar P., Singh Y., Sharma R. Swarm-Based UAV Communication Network: A Review of Challenges and Solutions. Procedia Computer Science. 2022. Vol. 198. P. 574–579. URL: https://doi.org/10.1016/j.procs.2021.12.299 DOI: https://doi.org/10.1016/j.procs.2021.12.299
14. Kovalyov A., Komarov M., Zabolotskiy A. Deployment of UAV Base Stations for Providing Wireless Coverage in Emergency Situations. Proc. of 2021 IEEE Int. Conf. on Emergency Science and Information Technology (ICESIT). 2021. P. 237–240. URL: https://doi.org/10.1109/ICESIT53202.2021.9629112
15. Han D., Xie J., Zhang Y. Fair Communications in UAV Networks for Rescue Applications. IEEE Internet of Things Journal. 2020. Vol. 7, no. 8. P. 7634–7646. URL: https://doi.org/10.1109/JIOT.2020.2995618
16. Fang Z., Savkin A. Strategies for Optimized UAV Surveillance in Various Tasks and Scenarios: A Review. Drones. 2024. Vol.8, no. 5. P. 193(1–25). URL: https://doi.org/10.3390/drones8050193 DOI: https://doi.org/10.3390/drones8050193
17. Autonomous UAV Safety Oriented Situation Monitoring and Evaluation System / Z. Shi et al. Drones. 2024. Vol. 8, no. 7. P.308(1–22). URL: https://doi.org/10.3390/drones8070308 DOI: https://doi.org/10.3390/drones8070308
18. UAV Applications for Monitoring and Management of Civil Infrastructures / A. Villarino et al. Infrastructures. 2025. Vol. 10, no. 5. P. 106(1–19). URL: https://doi.org/10.3390/infrastructures10050106 DOI: https://doi.org/10.3390/infrastructures10050106
19. Robotic-Biological Systems for Detection and Identification of Explosive Ordnance: Concept, General Structure, and Models / G. Fedorenko et al. Radioelectronic and Computer Systems. 2023. 2. P. 143–159. URL: https://doi.org/10.32620/reks.2023.2.12 DOI: https://doi.org/10.32620/reks.2023.2.12
20. Nikolaiev M., Novotarskyi M. Comparative Review of Drone Simulators. Information, Computing and Intelligent Systems. 2024. No. 4. P. 79–98. URL: https://doi.org/10.20535/2786-8729.4.2024.300614 DOI: https://doi.org/10.20535/2786-8729.4.2024.300614
21. Koenig N., Howard A. Design and Use Paradigms for Gazebo, an Open-Source Multi-Robot Simulator. Proc. of 2004 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS). 2004. P. 2149–2154. URL: https://doi.org/10.1109/IROS.2004.1389727 DOI: https://doi.org/10.1109/IROS.2004.1389727
22. Varga A., Hornig R. An Overview of the OMNeT++ Simulation Environment. Proc. of 1st Int. Conf. on Simulation Tools and Techniques (SIMUTools). 2008. P. 1–10. URL: https://dx.doi.org/10.4108/ICST.SIMUTOOLS2008.3027 DOI: https://doi.org/10.4108/ICST.SIMUTOOLS2008.3027
23. Baidya S., Shaikh Z., Levorato M. FlyNetSim: An Open Source Synchronized UAV Network Simulator Based on ns-3 and Ardupilot. Proc. of 21st ACM Int. Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems. 2018. P. 37–44. URL: https://doi.org/10.1145/3242102.3242118 DOI: https://doi.org/10.1145/3242102.3242118
24. Kudelski M., Gambardella L., Di Caro G. RoboNetSim: An Integrated Framework for Multi-Robot and Network Simulation. Robotics and Autonomous Systems. 2013. Vol. 61, no. 5. P. 483–496. URL: https://doi.org/10.1016/j.robot.2013.01.003 DOI: https://doi.org/10.1016/j.robot.2013.01.003
25. Annaz F. UAV Testbed Training Platform Development Using Panda3D. Industrial Robot – Int. J. 2015. Vol. 42, no. 5. P.450–456. URL: https://doi.org/10.1108/IR-01-2015-0017 DOI: https://doi.org/10.1108/IR-01-2015-0017
26. Robot Operating System 2: Design, Architecture, and Uses in the Wild / S. Macenski et al. Science Robotics. 2022. Vol. 7, no.66. P. eabm6074(1–8). URL: https://doi.org/10.1126/scirobotics.abm6074 DOI: https://doi.org/10.1126/scirobotics.abm6074
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Leonid Ostapenko, Vyacheslav Kharchenko

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.