HETEROGENEOUS UNMANNED SYSTEMS IN DANGEROUS SPACES: CLASSIFICATION, USE CASES SCENARIOS AND ACHIEVING SITUATIONAL AWARENESS

V. Kharchenko, H. Fesenko, I. Kliushnikov, E. Brezhniev, S. Stirenko, V. Mokhor

Èlektron. model. 2025, 47(3):46-65

https://doi.org/10.15407/emodel.47.03.046

ABSTRACT

The list of types of unmanned (crewless) vehicles that can form a heterogeneous unmanned system in various combinations is determined. A classification of heterogeneous unmanned systems and scenarios of their use is presented. Examples of such scenarios for heterogeneous unmanned systems consisting of three types of unmanned (crewless) vehicles are given, with the functions of each of these types detailed. The definition of a dangerous space is given and examples of it with one and three types of threats (multi-dangerous space) are given. The main operational tasks of overcoming dangerous spaces are formulated and the roles of heterogeneous unmanned systems and unmanned mobile depots in their implementation are shown. The ways to achieve situational awareness of dangerous spaces are formulated and the roles of heterogeneous unmanned systems and unmanned mobile depots in their implementation are shown. The correlation between the ways of achieving situational awareness of dangerous space and the tasks of overcoming it is presented. Directions for further research are formulated.

KEYWORDS

heterogeneous unmanned system, unmanned (crewless) vehicle, unmanned mobile depot, dangerous space, situational awareness

REFERENCES

  1. Huang, Y., Li, W., Ning, J., & Li, Z. (2023). Formation Control for UAV-USVs Heterogeneous System with Collision Avoidance Performance. Journal of Marine Science and Engineering11(12). https://doi.org/10.3390/jmse11122332
  2. Wu, J., Li, R., Li, J., Zou, M., & Huang, Z. (2023). Cooperative unmanned surface vehicles and unmanned aerial vehicles platform as a tool for coastal monitoring activities. Ocean and Coastal Management232, 106421 https://doi.org/10.1016/j.ocecoaman. 106421
  3. Wang, Y., Liu, W., Liu, J., & Sun, C. (2023). Cooperative USV-UAV marine search and rescue with visual navigation and reinforcement learning-based control. ISA Transactions137, 222- https://doi.org/10.1016/j.isatra.2023.01.007
  4. Santos, M.C., Bartlett, B., Schneider, V.E., Brádaigh, F.O., Blanck, B., Santos, P.C., Trslic P., Riordan J., Dooly, G. (2024). Cooperative Unmanned Aerial and Surface Vehicles for Extended Coverage in Maritime Environments. IEEE Access12, 9206- https://doi.org/ 10.1109/ACCESS.2024.3353046
  5. Li, Y., Li, S., Zhang, Y., Zhang, W., & Lu, H. (2023). Dynamic Route Planning for a USV-UAV Multi-Robot System in the Rendezvous Task with Obstacles. Journal of Intelligent and Robotic Systems: Theory and Applications107(4). https://doi.org/10.1007/ s10846-023-01830-5
  6. Liao, Y., Chen, X., Liu, J., Han, Y., Xu, N., & Yuan, Z. (2024). Cooperative UAV-USV MEC Platform for Wireless Inland Waterway Communications. IEEE Transactions on Consumer Electronics70(1), 3064-3076 https://doi.org/10.1109/TCE.2023.3327401
  7. Ennong, T., Ye, L., Teng, M., Yulei, L., Yueming, L., & Jian, C. (2024). Design and experiment of a sea-air heterogeneous unmanned collaborative system for rapid inspection tasks at sea. Applied Ocean Research, 143. https://doi.org/10.1016/j.apor.2023.103856
  8. Shirakura, N., Kiyokawa, T., Kumamoto, H., Takamatsu, J., & Ogasawara, T. (2021). Collection of Marine Debris by Jointly Using UAV-UUV with GUI for Simple Operation. IEEE Access9, 67432-67443 https://doi.org/10.1109/ACCESS.2021.3076110
  9. Nordin, M.H., Sharma, S., Khan, A., Gianni, M., Rajendran, S., & Sutton, R. (2022). Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines. Drones, 6(6), 137. https://doi.org/10.3390/drones6060137
  10. Hu, D., Gan, V.J.L., Wang, T., & Ma, L. (2022). Multi-agent robotic system (MARS) for UAV-UGV path planning and automatic sensory data collection in cluttered environments. Building and Environment, 221. https://doi.org/10.1016/j.buildenv.2022.109349
  11. Battistoni, P., Cantone, A.A., Martino, G., Passamano, V., Romano, M., Sebillo, M., & Vitiello, G. (2023). A Cyber-Physical System for Wildfire Detection and Firefigh­ting. Future Internet15(7), 237. https://doi.org/10.3390/fi15070237
  12. Chen, P., Luo, L., Guo, D., Luo, X., Li, X., & Sun, Y. (2024). Secure Task Offloading for Rural Area Surveillance Based on UAV-UGV Collaborations. IEEE Transactions on Vehicular Technology73(1), 923-937 https://doi.org/10.1109/TVT.2023.3307443
  13. Munasinghe, I., Perera, A., & Deo, R.C. (2024). A Comprehensive Review of UAV-UGV Collaboration: Advancements and Challenges. Journal of Sensor and Actuator Networks, 13(6), 81. https://doi.org/10.3390/jsan13060081
  14. Dinelli, C., Racette, J., Escarcega, M., Lotero, S., Gordon, J., Montoya, J., Dunaway, C., And­roulakis, V., Khaniani, H., Shao, S., Roghanchi, P., & Hassanalian, M. (2023). Configurations and Applications of Multi-Agent Hybrid Drone/Unmanned Ground Vehicle for Underground Environments: A Review. Drones7(2), 136. https://doi.org/10.3390/ drones7020136
  15. Ke, C., Chen, H., & Xie, L. (2023). Cross-Domain Fixed-Time Formation Control for an Air-Sea Heterogeneous Unmanned System with Disturbances. Journal of Marine Science and Engineering, 11(7). 1336. https://doi.org/10.3390/jmse11071336
  16. Li, J., Zhang, G., Jiang, C., & Zhang, W. (2023, October 1). A survey of maritime unmanned search system: Theory, applications and future directions. Ocean Engineering. Elsevier Ltd. https://doi.org/10.1016/j.oceaneng.2023.115359
  17. Barilaro, L. (2023). BEA: Overview of a multi-unmanned vehicle system for diver assistance. In Aeronautics and Astronautics. Materials Research Forum LLC. https://doi.org/ 21741/9781644902813-53
  18. Cao, X., Liu, W., & Ren, L. (2024). Underwater Target Capture based on Heterogeneous Unmanned System Collaboration. IEEE Transactions on Intelligent Vehicles. https://doi.org/10.1109/TIV.2024.3362358
  19. Chen, Y., Wang, J., Zhu, S., Gu, Y., Dai, H., Xu, J., Zhu, Y., & Wu, T. (2022). Know­ledge Graph Construction for Foreign Military Unmanned Systems. In Communications in Computer and Information Science(pp. 127-137). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-8300-9_14
  20. Park, S.-B., Ha, J.-U., & Park, J.-K. (2021). A Study on the Obstacle Collision Avoidance Using Leader-Follower Formation Control Algorithm of Multiple Unmanned Vehicles in Ground Warfare. Journal of the Korean Association of Defense Industry Studies, 28(3), 61- https://doi.org/10.52798/kadis.2021.28.3.5
  21. On Approval of the Rules of Flight Operations by Unmanned Aircraft Systems of the State Aviation of Ukraine, Order of the Ministry of Defense of Ukraine No. 661 (2020) (Ukraine). https://zakon.rada.gov.ua/laws/show/z0031-17#Text
  22. Bouraou, N.I., & Zolotarov, Y.O. (2023). Systems of Visualization of The Movement of Unmanned Underwater Apparatus. Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences1(3), 83- https://doi.org/10.32782/2663-5941/ 2023.3.1/14
  23. Moshref-Javadi, M., Hemmati, A., & Winkenbach, M. (2020). A truck and drones model for last-mile delivery: A mathematical model and heuristic approach. Applied Mathematical Modelling80, 290-318 https://doi.org/10.1016/j.apm.2019.11.020
  24. Horbulin, V.P., Hulianytskyi, L.F., & Sergienko, I.V. (2020). Optimization of UAV Team Routes in the Presence of Alternative and Dynamic Depots. Cybernetics and Systems Analysis56(2), 195- https://doi.org/10.1007/s10559-020-00235-8
  25. Fesenko, H., Illiashenko, O., Kharchenko, V., Kliushnikov, I., Morozova, O., Sachenko, A., & Skorobohatko, S. (2023). Flying Sensor and Edge Network-Based Advanced Air Mobi­lity Systems: Reliability Analysis and Applications for Urban Monitoring. Drones, 7(7), 409. URL: https://doi.org/10.3390/drones7070409.
  26. Kharchenko, V., Kliushnikov, I., Rucinski, A., Fesenko, H., & Illiashenko, O. (2022). UAV Fleet as a Dependable Service for Smart Cities: Model-Based Assessment and Smart Cities, 5(3), 1151-1178. URL: https://doi.org/10.3390/smartcities 5030058
  27. Illiashenko, O., Kharchenko, V., Babeshko, I., Fesenko, H., & Di Giandomenico, F. (2023). Security-Informed Safety Analysis of Autonomous Transport Systems Conside­ring AI-Powered Cyberattacks and Protection / Entropy. 2023. Vol. 25, no. 8. P. 1123. URL:  https://doi.org/10.3390/e25081123.
  28. Fesenko, H., Illiashenko, O., Kharchenko, V., Leichenko, K., Sachenko, A., & Scislo, L. (2024). Methods and Software Tools for Reliable Operation of Flying LiFi Networks in Destruction Conditions. Sensors, 24(17), 5707. URL:  https://doi.org/10.3390/s24175707.
  29. Fedorenko, G., Fesenko, H., Kharchenko, V., Kliushnikov, I., & Tolkunov, I. (2023) Robotic-biological systems for detection and identification of explosive ordnance: concept, general structure, and models. Radioelectronic and Computer Systems, 2, 143- URL:  https://doi.org/10.32620/reks.2023.2.12.
  30. Munir, A., Aved, A., & Blasch, E. (2022) Situational Awareness: Techniques, Challenges, and Prospects. AI, 3(1), 55-77. URL:  https://doi.org/10.3390/ai3010005.

Full text: PDF