Cooperative Decision-Making for Drone Swarms
Resumo
Unmanned Aerial Vehicles (UAVs) are being researched for their potential in applications like search and rescue, and defense missions. The goal is to enhance the intelligence, communication, and strategic organization. Decision-making techniques enable intelligent UAV decisions, freeing human commanders to focus on higher-level decisions. This research focuses on defense and search and rescue scenarios, and combines AI-based decision-making with UAVs. The study analyze the Loyal Wingman concept in a defense scenario. Also, we propose a solution for a drone swarm to cooperatively search for people in a rescue scenario. Our results demonstrate the effectiveness of distributed decision-making methods in solving problems in both scenarios.Referências
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Colledanchise, M. and Ogren, P. (2018). Behavior Trees in Robotics and AI: An Introduction. Chapman & Hall/CRC Press.
Garcia-Aunon, P., del Cerro, J., and Barrientos, A. (2019). Behavior-based control for an aerial robotic swarm in surveillance missions. Sensors, 19(20).
Giacomossi, L., Maximo, M. R., Sundelius, N., Funk, P., Brancalion, J. F., and Sohlberg, R. (2023). Cooperative search and rescue with drone swarm. In IAI2023 International Congress and Workshop on Industrial AI.
Giacomossi, L., Schwanz Dias, S., Brancalion, J., and Maximo, M. (2021a). Cooperative and decentralized decision-making for loyal wingman UAVs. In IEEE Latin American Robotics Symposium (LARS), pages 78–83. IEEE.
Giacomossi, L., Souza, F., Cortes, R. G., Mirko M. Cortez, H., Ferreira, C., Marcondes, C. A. C., Loubach, D. S., Sbruzzi, E. F., Verri, F. A. N., Marques, J. C., Pereira, L. A., Maximo, M. R. O. A., and Curtis, V. V. (2021b). Autonomous and collective intelligence for uav swarm in target search scenario. In 2021 Latin American Robotics Symposium (LARS), pages 72–77. IEEE.
Iovino, M., Scukins, E., Styrud, J., Ögren, P., and Smith, C. (2022). A survey of behavior trees in robotics and ai. Robotics and Autonomous Systems, page 104096.
Mahadevan, S. and Connell, J. (1992). Automatic programming of behavior-based robots using reinforcement learning. Artificial Intelligence, 55(2):311–365.
Munkres, J. (1957). Algorithms for the assignment and transportation problems. Journal of the society for industrial and applied mathematics, 5(1):32–38.
Ogren, P. (2012). Increasing modularity of uav control systems using computer game behavior trees. AIAA Guidance, Navigation, and Control Conference, pages AIAA 2012–4458.
Ricardo, J. A., Giacomossi, L., Trentin, J. F. S., Brancalion, J. F. B., Maximo, M. R. O. A., and Santos, D. A. (2023). Cooperative threat engagement using drone swarms. IEEE Access, 11:9529–9546.
Ricardo Jr, J. A. and dos Santos, D. A. (2023). Robust collision-free guidance and control for fully actuated multirotor aerial vehicles. PREPRINT (Version 1) available at Research Square.
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Stone, L. (1976). Theory of Optimal Search. ISSN. Elsevier Science.
Box, G. E. and Tiao, G. C. (2011). Bayesian inference in statistical analysis. John Wiley & Sons.
Buckland, M. (2004). Programming Game AI by Example. Jones & Bartlett Publishers, Burlington, Massachusetts, USA.
Burkard, R. E. and Çela, E. (1999). Linear Assignment Problems and Extensions, pages 75–149. Springer US, Boston, MA.
Choset, H., Lynch, K., Hutchinson, S., Kantor, G., and Burgard, W. (2005). Principles of Robot Motion: Theory, Algorithms, and Implementations. Intelligent Robotics and Autonomous Agents series. MIT Press.
Colledanchise, M. and Ogren, P. (2018). Behavior Trees in Robotics and AI: An Introduction. Chapman & Hall/CRC Press.
Garcia-Aunon, P., del Cerro, J., and Barrientos, A. (2019). Behavior-based control for an aerial robotic swarm in surveillance missions. Sensors, 19(20).
Giacomossi, L., Maximo, M. R., Sundelius, N., Funk, P., Brancalion, J. F., and Sohlberg, R. (2023). Cooperative search and rescue with drone swarm. In IAI2023 International Congress and Workshop on Industrial AI.
Giacomossi, L., Schwanz Dias, S., Brancalion, J., and Maximo, M. (2021a). Cooperative and decentralized decision-making for loyal wingman UAVs. In IEEE Latin American Robotics Symposium (LARS), pages 78–83. IEEE.
Giacomossi, L., Souza, F., Cortes, R. G., Mirko M. Cortez, H., Ferreira, C., Marcondes, C. A. C., Loubach, D. S., Sbruzzi, E. F., Verri, F. A. N., Marques, J. C., Pereira, L. A., Maximo, M. R. O. A., and Curtis, V. V. (2021b). Autonomous and collective intelligence for uav swarm in target search scenario. In 2021 Latin American Robotics Symposium (LARS), pages 72–77. IEEE.
Iovino, M., Scukins, E., Styrud, J., Ögren, P., and Smith, C. (2022). A survey of behavior trees in robotics and ai. Robotics and Autonomous Systems, page 104096.
Mahadevan, S. and Connell, J. (1992). Automatic programming of behavior-based robots using reinforcement learning. Artificial Intelligence, 55(2):311–365.
Munkres, J. (1957). Algorithms for the assignment and transportation problems. Journal of the society for industrial and applied mathematics, 5(1):32–38.
Ogren, P. (2012). Increasing modularity of uav control systems using computer game behavior trees. AIAA Guidance, Navigation, and Control Conference, pages AIAA 2012–4458.
Ricardo, J. A., Giacomossi, L., Trentin, J. F. S., Brancalion, J. F. B., Maximo, M. R. O. A., and Santos, D. A. (2023). Cooperative threat engagement using drone swarms. IEEE Access, 11:9529–9546.
Ricardo Jr, J. A. and dos Santos, D. A. (2023). Robust collision-free guidance and control for fully actuated multirotor aerial vehicles. PREPRINT (Version 1) available at Research Square.
Santos, D. A. and Bezerra, J. A. (2022). On the control allocation of fully actuated multirotor aerial vehicles. Aerospace Science and Technology, 122:107424.
Stone, L. (1976). Theory of Optimal Search. ISSN. Elsevier Science.
Publicado
09/10/2023
Como Citar
GIACOMOSSI JR., Luiz; MAXIMO, Marcos R. O. A.; BRANCALION, José F. B..
Cooperative Decision-Making for Drone Swarms. In: CONCURSO DE TESES E DISSERTAÇÕES EM ROBÓTICA - CTDR (MESTRADO) - SIMPÓSIO BRASILEIRO DE ROBÓTICA E SIMPÓSIO LATINO-AMERICANO DE ROBÓTICA (SBR/LARS), 15. , 2023, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
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p. 73-84.
DOI: https://doi.org/10.5753/sbrlars_estendido.2023.235339.