Abstract
This paper describes and evaluates the use of Jason BDI agents to make the high-level control and the coordination of a swarm of autonomous unmanned aerial vehicles (UAVs). The UAVs in the swarm work together searching and extinguishing fire spots in a simulated forest firefighting scenario. This problem was presented by the 2022 SARC–BARINET aerospace competition, which makes use of the ROS/Gazebo simulation environment. ROS is also used here to perform the low-level UAV’s control. Our solution requires a minimum of 2 UAVs and can be easily scaled. We were able to successfully complete the given mission using up to 8 UAVs. Additional experiments devoted for performance-data collection were conducted using swarms with 4, 6, and 8 UAVs. Obtained results are presented and discussed along the paper.
This work was partially supported by the Brazilian funding agencies FAPESC, CAPES, and CNPq. Part of Leandro Buss Becker’s work, while at Manchester, was supported by The Royal Academy of Engineering through its Chair in Emerging Technologies scheme. Jomi Hübner was supported by CNPq, grant 402711/2022-0.
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The full agent code is available for download at https://github.com/iagosilvestre/start-UFSC.
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Silvestre, I., de Lima, B., Dias, P.H., Buss Becker, L., Hübner, J.F., de Brito, M. (2023). UAV Swarm Control and Coordination Using Jason BDI Agents on Top of ROS. In: Mathieu, P., Dignum, F., Novais, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Cognitive Mimetics. The PAAMS Collection. PAAMS 2023. Lecture Notes in Computer Science(), vol 13955. Springer, Cham. https://doi.org/10.1007/978-3-031-37616-0_19
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