A Communication System for Dynamic Leader Selection in Distributed UAV Swarm Architecture

Yıl 2024, Cilt: 14 Sayı: 1, 96 - 102, 30.06.2024

Abdulmelik Bekmez , Kadir Aram

https://doi.org/10.36222/ejt.1434751

Öz

Distributed swarm robot systems are made up of several robots that communicate with one another and often work together to complete a task or reach a predetermined objective. These systems frequently consist of many platforms, like unmanned aerial aircraft, mobile robots, or other types of vehicles.
This paper offers a comprehensive exploration of the design, modeling, and real-world hardware and software implementation of a distributed swarm system. The decision was made to employ standard Pixhawk hardware for the swarm agents. Pixhawk, a freely available hardware and software platform for autonomous flight control, is commonly utilized in autonomous cars, multirotor vehicles, drones, and various robotic applications. Operating autonomously from the ground control station, swarm agents dynamically identify leaders during operation and execute leader tracking navigation to model swarm behavior. Ensuring generality and dynamism in all protocols and communication was a primary focus during the research phase. To maintain this dynamism, each protocol and communication process is implemented in distinct threads on the computer, and synchronization is achieved through synchronization primitives, shared memory, and interthread communication.

Anahtar Kelimeler

Leader-Follower, Communication, Distributed, Robotics, Formation Control

Kaynakça

• [1] W. Luo, S. S. Khatib, S. Nagavalli, N. Chakraborty, and K. Sycara, “Asynchronous distributed information leader selection in robotic swarms,” in 2015 IEEE International Conference on Automation Science and Engineering (CASE), 2015, pp. 606–611. doi: 10.1109/CoASE.2015.7294145.
• [2] M. Carpentiero, L. Gugliermetti, M. Sabatini, and G. B. Palmerini, “A swarm of wheeled and aerial robots for environmental monitoring,” in 2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), 2017, pp. 90–95. doi: 10.1109/ICNSC.2017.8000073.
• [3] M. Duarte et al., “Application of swarm robotics systems to marine environmental monitoring,” in OCEANS 2016 - Shanghai, 2016, pp. 1–8. doi: 10.1109/OCEANSAP.2016.7485429.
• [4] J. Asbach, S. Chowdhury, and K. Lewis, “Using an Intelligent UAV Swarm in Natural Disaster Environments,” in International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2018, p. V02AT03A013.
• [5] J. Scherer et al., “An autonomous multi-UAV system for search and rescue,” in Proceedings of the first workshop on micro aerial vehicle networks, systems, and applications for civilian use, 2015, pp. 33–38.
• [6] Y. Song et al., “Distributed swarm system with hybrid-flocking control for small fixed-wing UAVs: Algorithms and flight experiments,” Expert Syst. Appl., vol. 229, p. 120457, 2023.
• [7] S. Dey and H. Xu, “Intelligent Distributed Swarm Control for Large-Scale Multi-UAV Systems: A Hierarchical Learning Approach,” Electronics, vol. 12, no. 1, p. 89, 2022.
• [8] Y. Jia, M. Chen, Y. Gao, and H. Wang, “A Distributed Method to Form UAV Swarm based on Moncular Vision,” in 2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS), 2023, pp. 41–48.
• [9] B. Zhu and Y. Deng, “Distributed UAV swarm control framework with limited interaction for obstacle avoidance,” Aircr. Eng. Aerosp. Technol., no. ahead-of-print, 2022.
• [10] R. Rafifandi, D. L. Asri, E. Ekawati, and E. M. Budi, “Leader--follower formation control of two quadrotor UAVs,” SN Appl. Sci., vol. 1, pp. 1–12, 2019.
• [11] N. H. M. Li and H. H. T. Liu, “Formation UAV flight control using virtual structure and motion synchronization,” in 2008 American Control Conference, 2008, pp. 1782–1787.
• [12] D. Xu, X. Zhang, Z. Zhu, C. Chen, P. Yang, and others, “Behavior-based formation control of swarm robots,” Math. Probl. Eng., vol. 2014, 2014.
• [13] H. Zhang, G. Zhang, R. Yang, Z. Feng, and W. He, “Resilient Formation Reconfiguration for Leader--Follower Multi-UAVs,” Appl. Sci., vol. 13, no. 13, p. 7385, 2023.
• [14] A. Lazri, E. Restrepo, and A. Lor\’\ia, “Robust leader-follower formation control of autonomous vehicles with unknown leader velocities,” in 2023 European Control Conference (ECC), 2023, pp. 1–6.
• [15] J.-H. Lee et al., “Unmanned Surface Vehicle Using a Leader--Follower Swarm Control Algorithm,” Appl. Sci., vol. 13, no. 5, p. 3120, 2023.
• [16] N. Pauli and W. Fichter, “Leader-Follower Formation Control with Longitudinal Separation along Lateral and Vertical Shifted Follower Paths,” in AIAA SCITECH 2023 Forum, 2023, p. 484.
• [17] L.-B. Wee and Y.-C. Paw, “Simultaneous Mapping Localization and Path Planning for UAV Swarm,” in 2023 IEEE Aerospace Conference, 2023, pp. 1–6.
• [18] H. Y. Liu, J. Chen, K. H. Huang, G. Q. Cheng, and R. Wang, “UAV swarm collaborative coverage control using GV division and planning algorithm,” Aeronaut. J., vol. 127, no. 1309, pp. 446–465, 2023.
• [19] L. Meier, P. Tanskanen, F. Fraundorfer, and M. Pollefeys, “Pixhawk: A system for autonomous flight using onboard computer vision,” in 2011 ieee international conference on robotics and automation, 2011, pp. 2992–2997.
• [20] A. Allouch, O. Cheikhrouhou, A. Koubâa, M. Khalgui, and T. Abbes, “MAVSec: Securing the MAVLink Protocol for Ardupilot/PX4 Unmanned Aerial Systems,” in 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019, pp. 621–628. doi: 10.1109/IWCMC.2019.8766667.
• [21] L. Meier, D. Honegger, and M. Pollefeys, “PX4: A node-based multithreaded open source robotics framework for deeply embedded platforms,” in 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015, pp. 6235–6240. doi: 10.1109/ICRA.2015.7140074.
• [22] A. BEKMEZ and A. Kadir, “Three Dimensional Formation Control of Unmanned Aerial Vehicles in Obstacle Environments,” Balk. J. Electr. Comput. Eng., vol. 11, no. 4, pp. 387–394, 2023.
• [23] M. Quigley et al., “ROS: an open-source Robot Operating System,” in ICRA workshop on open source software, 2009, p. 5.
• [24] L. Joseph and J. Cacace, Mastering ROS for Robotics Programming: Design, build, and simulate complex robots using the Robot Operating System. Packt Publishing Ltd, 2018.
• [25] S. Macenski, T. Foote, B. Gerkey, C. Lalancette, and W. Woodall, “Robot Operating System 2: Design, architecture, and uses in the wild,” Sci. Robot., vol. 7, no. 66, p. eabm6074, 2022.
• [26] J. J. Lopez Escobar, R. P. Diaz-Redondo, and F. Gil-Castineira, “Unleashing the power of decentralized serverless IoT dataflow architecture for the Cloud-to-Edge Continuum: a performance comparison,” Ann. Telecommun., pp. 1–14, 2024.
• [27] A. Corsaro et al., “Zenoh: Unifying Communication, Storage and Computation from the Cloud to the Microcontroller,” vol. DSD 2023, 2023.
• [28] Z. Tüfekçi and G. Erdemir, “Experimental Comparison of Global Planners for Trajectory Planning of Mobile Robots in an Unknown Environment with Dynamic Obstacles,” in 2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2023, pp. 1–6.