Advancing Drone Swarm Simulation: A Comprehensive System for Real-Time Control and Dynamic Interaction

[1] CHEN, W. – LIU, J. – GUO, H. – KATO, N.: Toward robust and intelligent drone swarm: Challenges and future directions. IEEE Network. 34, 278-283 (2020) Search in Google Scholar

[2] CASADO, R. – BERMÚDEZ, A.: A simulation framework for developing autonomous drone navigation systems. Electronics. 10, 7 (2020) Search in Google Scholar

[3] SORIA, E. – SCHIANO, F. – FLOREANO, D.: SwarmLab: A MATLAB drone swarm simulator. 2020 IEEE/RSJ International Conference On Intelligent Robots And Systems (IROS). pp. 8005-8011 (2020) Search in Google Scholar

[4] LI, W. – HU, Y. – WANG, F. – WANG, C. – ZHANG, W.: Simulation System Design of Unmanned Aerial Vehicle Swarm. 2022 IEEE International Conference On Unmanned Systems (ICUS). pp. 109-114 (2022) Search in Google Scholar

[5] PYKE, L. – STARK, C.: Dynamic pathfinding for a swarm intelligence based UAV control model using particle swarm optimisation. Frontiers In Applied Mathematics And Statistics. 7 pp. 744955 (2021) Search in Google Scholar

[6] QAMAR, S. – KHAN, S.– ARSHAD, M. – QAMAR, M. – KHAN, A.: Autonomous drone swarm navigation and multi-target tracking in 3D environments with dynamic obstacles. ArXiv Preprint ArXiv:2202.06253. (2022) Search in Google Scholar

[7] LEE, S. – YANG, J. – LEE, B.: Drone simulation technologies. Electronics And Telecommunications Trends. 35, 81-90 (2020) Search in Google Scholar

[8] SAFFRE, F. – HILDMANN, H. – KARVONEN, H.: The design challenges of drone swarm control. International Conference On Human-computer Interaction. pp. 408-426 (2021) Search in Google Scholar

[9] GRIGOROPOULOS, N. – LALIS, S.: Simulation and digital twin support for managed drone applications. 2020 IEEE/ACM 24th International Symposium On Distributed Simulation And Real Time Applications (DS-RT). pp. 1-8 (2020) Search in Google Scholar

[10] ROCCA, R.: Fault animation with 3D model integrating drone and satellite images. EGU General Assembly Conference, 2021. Proceedings. Doi. 10 (2021) Search in Google Scholar

[11] WISNIEWSKI, M. – RANA, Z.: & Petrunin, I. Drone model classification using convolutional neural network trained on synthetic data. Journal Of Imaging. 8, 218 (2022) Search in Google Scholar

[12] HASSIJA, V. – CHAMOLA, V. – AGRAWAL, A. – GOYAL, A. – LUONG, N. – NIYATO, D. – YU, F. – GUIZANI, M.: Fast, reliable, and secure drone communication: A comprehensive survey. IEEE Communications Surveys & Tutorials. 23, 2802-2832 (2021) Search in Google Scholar

[13] HASSAN, G. – HUSSIEN, N. – MOHIALDEN, Y.: Python TCP/IP libraries: A Review. International Journal Papier Advance And Scientific Review. 4, 10-15 (2023) Search in Google Scholar

[14] NASIR, A.: Latency optimization of UAV-enabled MEC system for virtual reality applications under rician fading channels. IEEE Wireless Communications Letters. 10, 1633-1637 (2021) Search in Google Scholar