Drone Wars 3D: A Game-Based Simulation Platform for Testing Aerial Defence Strategies Against Drone Swarms

Authors

  • Gökhan KARADENİZ Istanbul Technical University, Faculty of Computer and Informatics Engineering, Gameand Interaction Technologies
  • Ahmet ÖZCAN National Defence University, Atatürk Strategic Studies and Graduate Institute, Department of Computer Engineering
  • Mehmet BAYRAM National Defence University, Atatürk Strategic Studies and Graduate Institute, Department of Industrial Engineering
  • Gökhan İNCE Istanbul Technical University, Faculty of Computer and Informatics Engineering, Gameand Interaction Technologies

Keywords:

drone, swarm, defence, simulation, Unity, game, serious game

Abstract

Unmanned aerial vehicles (UAVs), commonly referred to as "drones", have received a notable surge in recent years, particularly within military contexts. In this study, a simulation platform was developed to assess the viability of employing drone swarms as a defensive mechanism against opposing drones. The study encompasses diverse tactical approaches including the arrangement of attacking and defending drones, the role of drone launchers, and the critical factors of detection and response time. The results show the effectiveness of drone swarms, machine guns, anti-aircraft guns, laser guns and surface-to-air missiles against swarms of attacking drones. The findings provide a comprehensive insight into the potential performance of these countermeasures, laying the groundwork for the formulation of effective defence strategies against the emerging threat of drone swarms.

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References

Clarivate, Web Of Science, webofknowledge.com [Online]. Available: http://apps.webofknowledge.com/. [Accessed: Jul. 04, 2023].

K. Aloui, M. Hammadi, A. Guizani, M. Haddar and T. Soriano, A new SysML Model for UAV Swarm Modeling: UavSwarmML, 2022 IEEE International Systems Conference (SysCon), Montreal, QC, Canada, pp. 1-8 (2022).

A. Lukina et al., Formation Control and Persistent Monitoring in the OpenUAV Swarm Simulator on the NSF CPS-VO, 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS), Porto, Portugal, pp. 353-354 (2018).

Open-UAV Project, “OpenUAV Project”, github.com [Online]. Available: https://github.com/Open-UAV. [Accessed: May 04, 2023].

W. Chen, J. Liu and H. Guo, Achieving Robust and Efficient Consensus for Large-Scale Drone Swarm, in IEEE Transactions on Vehicular Technology, vol. 69, no. 12, pp. 15867-15879, (2020).

Z. Kallenborn, InfoSwarms: Drone Swarms and Information Warfare, The US Army War College Quarterly: Parameters, vol. 52, no. 2, pp. 87–102, (2022).

J. -H. Jeong, D. -H. Lee, H. -J. Ahn and S. -W. Lee, Towards Brain-Computer Interfaces for Drone Swarm Control, 2020 8th International Winter Conference on Brain-Computer Interface (BCI), Gangwon, Korea (South), pp. 1-4, (2020).

A. Mairaj, A. I. Baba, and A. Y. Javaid, Application specific drone simulators: Recent advances and challenges, Simulation Modelling Practice and Theory, vol. 94, pp. 100–117, ( 2019).

E. Soria, F. Schiano and D. Floreano, SwarmLab: a Matlab Drone Swarm Simulator, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA, pp. 8005-8011, (2020).

L. Jeroncic, Drone Swarm Simulator, Tromsø: UiT The Arctic University of Norway, (2021).

P. K. Kumar, GUI Enhancements and AI Interfaces for Swarm Simulation and Flight Learning of Unmanned Aerial Vehicles, New York:State University of New York at Buffalo, (2021).

S. Devgan, S. Walia, V. Khemchandani and S. Chandra, Multi/Swarm Drone Surveillance and Monitoring System using VR simulation, 2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT), New Delhi, India, pp. 1-6, (2022).

N. Bhamu, H. Verma, A. Dixit, B. Bollard, and S. R. Sarangi, SmrtSwarm: A Novel Swarming Model for Real-World Environments, Drones, vol. 7, no. 9, p. 573, (2023).

C. Abt Clark, Serious games, New York : Viking Press, (1970).

V. Mittal and A. Davidson, Combining Wargaming With Modeling and Simulation to Project Future Military Technology Requirements, in IEEE Transactions on Engineering Management, vol. 68, no. 4, pp. 1195-1207, (2021).

D. M. Edwards, Simulated Laser Weapon System Decision Support to Combat Drone Swarms with Machine Learning, Monterey: Naval Postgraduate School, (2021).

Jari Laarni, Antti Väätänen, H. Karvonen, T. Lastusilta, and Fabrice Saffre, Development of a Concept of Operations for a Counter-Swarm Scenario, Lecture Notes in Computer Science, pp. 49–63, (2022).

S. M. Williams, Swarm Weapons: Demonstrating a Swarm Intelligent Algorithm for Parallel Attack, Kansas:US Army School for Advanced Military Studies Fort Leavenworth United States, (2018).

O. Kmia, “The technical and legal challenges of Anti-Drone Systems”, fstoppers.com [Online], Avaliable: https://fstoppers.com/aerial/technical-and-legal-challenges-anti-drone-systems-193666 [Accessed Nov. 19, 2023].

L. Bayındır, A review of swarm robotics tasks, Neurocomputing, vol. 172, pp. 292–321, (2016).

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Published

05-04-2024

How to Cite

[1]
G. KARADENİZ, A. ÖZCAN, M. BAYRAM, and G. İNCE, “Drone Wars 3D: A Game-Based Simulation Platform for Testing Aerial Defence Strategies Against Drone Swarms”, JAST, vol. 17, no. Special Issue, pp. 182–207, Apr. 2024.