Arquitetura de Simulação de Missões com Drones com Aspectos Mais Realistas de Comunicação Ar-Terra
Resumo
Os Veículos Aéreos Não Tripulados (ou UAV, do inglês Unmanned Aerial Vehicles) tiveram um crescimento significativo devido a seus preços acessíveis, disponibilidade e facilidade de operação. Esses benefícios de operabilidade levaram a sua introdução em muitas aplicações civis, incluindo vigilância, monitoramento remoto, operações de socorro, além do uso recreativo. Para aplicações críticas, uma plataforma realista de simulação de missão de UAV, incluindo modelos precisos para prever o alcance e a qualidade da comunicação entre o UAV e a estação terrestre, é de grande valia para garantir a eficácia e a segurança do voo. Nossos estudos mostraram que as plataformas de simulação são, em geral, simplificadas quanto aos modelos de comunicação. Neste artigo, propomos uma arquitetura de simulação baseada no SITL ArduPilot que introduz modelos de comunicação mais precisos.
Referências
ArduPilot (2022a). Mavproxy. Available at https://ardupilot.org/mavproxy/.
ArduPilot (2022b). Mission planner. Available at https://ardupilot.org/planner/.
ArduPilot (2022c). Sitl simulator(software in the loop. Available at https://ardupilot.org/dev/docs/sitl-simulator-software-in-the-loop.html.
Bastos, C. A. M., Passos, D., Barbosa, W. M., dos Santos Felipe, Y. S., Loureiro, T. B., dos Santos Dias, G., and Passos, F. G. O. (2022). Drones for civil defense: a case study in the city of niterói. In 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management.
Coopmans, C., Podhradský, M., and Hoffer, N. V. (2015). Software and hardware-in-the loop verification of flight dynamics model and flight control simulation of a fixed-wing unmanned aerial vehicle. In 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS).
DJI (2022). Dji flight simulator. Available at https://www.dji.com/br/simulator.
Dronecode, P. (2022). Mavlink. Available at https://mavlink.io/en/.
Feng, Q., McGeehan, J., Tameh, E., and Nix, A. (2006). Path loss models for air-to-ground radio channels in urban environments. In 2006 IEEE 63rd Vehicular Technology Conference, volume 6, pages 2901-2905.
Gazebo (2022). Gazebo. Available at https://gazebosim.org/home.
Koubâa, A., Allouch, A., Alajlan, M., Javed, Y., Abdelfettah, and Khalgui, M. (2019). Micro air vehicle link (mavlink) in a nutshell: A survey. IEEE Access, vol. 7, pp. 87658 87680, 2019.
Lacage, M. and Henderson, T. R. (2006). Yet another network simulator. Proceedings of the 2006 Workshop on ns-3.
Lassabe, F., Canalda, P., Chatonnay, P., Spies, F., and Baala, O. (2005). A friis-based calibrated model for wifi terminals positioning. In Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks, pages 382-387.
Lee, B. j., hwan Lee, S., and Rhee, S. h. (2010). Rate-adaptive mac protocol for efficient use of channel resource in wireless multi-hop networks. In 2010 Second International Conference on Ubiquitous and Future Networks (ICUFN), pages 115-120.
Motlagh, N. H., Taleb, T., and Arouk, O. (2016). Low-altitude unmanned aerial vehicles-based internet of things services: Comprehensive survey and future perspectives. IEEE Internet of Thigs Journal.
Nekrasov, M., Allen, R., Artamonova, I., and Belding, E. (2019). Optimizing 802.15.4 outdoor iot sensor networks for aerial data collection. Sensors.
Research, M. (2022). Airsim. Available at https://microsoft.github.io/AirSim/.
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., (Senior Member, I., Dou, Z., Almaita, E., Khalil, I., Othman, N. S., Khreishah, A., Guizani, M., and (Fellow, I. (2019). Unmanned aerial vehicles (uavs): A survey on civil applications and key research challenges. IEEE Access, vol. 7, pp. 48572 48634, 2019.
Siddiqui, S. A., Fatima, N., and Ahmad, A. (2019). Comparative analysis of propagation path loss models in lte networks. In 2019 International Conference on Power Electronics, Control and Automation (ICPECA), pages 1-3.
Software, K. E. (2022). Realflight simulator. Available at https://www.realflight.com/.
Vergouw, B., Nagel, H., Bondt, G., and Curters, B. (2016). Drone Technology: Types, Payloads, Applications, Frequency Spectrum Issues and Future Developments, pages 21-45. T.M.C. Asser Press, The Hague.
ArduPilot (2022b). Mission planner. Available at https://ardupilot.org/planner/.
ArduPilot (2022c). Sitl simulator(software in the loop. Available at https://ardupilot.org/dev/docs/sitl-simulator-software-in-the-loop.html.
Bastos, C. A. M., Passos, D., Barbosa, W. M., dos Santos Felipe, Y. S., Loureiro, T. B., dos Santos Dias, G., and Passos, F. G. O. (2022). Drones for civil defense: a case study in the city of niterói. In 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management.
Coopmans, C., Podhradský, M., and Hoffer, N. V. (2015). Software and hardware-in-the loop verification of flight dynamics model and flight control simulation of a fixed-wing unmanned aerial vehicle. In 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS).
DJI (2022). Dji flight simulator. Available at https://www.dji.com/br/simulator.
Dronecode, P. (2022). Mavlink. Available at https://mavlink.io/en/.
Feng, Q., McGeehan, J., Tameh, E., and Nix, A. (2006). Path loss models for air-to-ground radio channels in urban environments. In 2006 IEEE 63rd Vehicular Technology Conference, volume 6, pages 2901-2905.
Gazebo (2022). Gazebo. Available at https://gazebosim.org/home.
Koubâa, A., Allouch, A., Alajlan, M., Javed, Y., Abdelfettah, and Khalgui, M. (2019). Micro air vehicle link (mavlink) in a nutshell: A survey. IEEE Access, vol. 7, pp. 87658 87680, 2019.
Lacage, M. and Henderson, T. R. (2006). Yet another network simulator. Proceedings of the 2006 Workshop on ns-3.
Lassabe, F., Canalda, P., Chatonnay, P., Spies, F., and Baala, O. (2005). A friis-based calibrated model for wifi terminals positioning. In Sixth IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks, pages 382-387.
Lee, B. j., hwan Lee, S., and Rhee, S. h. (2010). Rate-adaptive mac protocol for efficient use of channel resource in wireless multi-hop networks. In 2010 Second International Conference on Ubiquitous and Future Networks (ICUFN), pages 115-120.
Motlagh, N. H., Taleb, T., and Arouk, O. (2016). Low-altitude unmanned aerial vehicles-based internet of things services: Comprehensive survey and future perspectives. IEEE Internet of Thigs Journal.
Nekrasov, M., Allen, R., Artamonova, I., and Belding, E. (2019). Optimizing 802.15.4 outdoor iot sensor networks for aerial data collection. Sensors.
Research, M. (2022). Airsim. Available at https://microsoft.github.io/AirSim/.
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., (Senior Member, I., Dou, Z., Almaita, E., Khalil, I., Othman, N. S., Khreishah, A., Guizani, M., and (Fellow, I. (2019). Unmanned aerial vehicles (uavs): A survey on civil applications and key research challenges. IEEE Access, vol. 7, pp. 48572 48634, 2019.
Siddiqui, S. A., Fatima, N., and Ahmad, A. (2019). Comparative analysis of propagation path loss models in lte networks. In 2019 International Conference on Power Electronics, Control and Automation (ICPECA), pages 1-3.
Software, K. E. (2022). Realflight simulator. Available at https://www.realflight.com/.
Vergouw, B., Nagel, H., Bondt, G., and Curters, B. (2016). Drone Technology: Types, Payloads, Applications, Frequency Spectrum Issues and Future Developments, pages 21-45. T.M.C. Asser Press, The Hague.
Publicado
22/05/2023
Como Citar
HILARIO, Bruno A.; PASSOS, Diego; GUERRA, Raphael.
Arquitetura de Simulação de Missões com Drones com Aspectos Mais Realistas de Comunicação Ar-Terra. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 41. , 2023, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 99-112.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2023.442.
