Sensoriamento remoto para culturas agrícolas baseado em um quadricóptero de baixo custo
DOI:
https://doi.org/10.18046/syt.v13i34.2092Palavras-chave:
Quadricóptero, Sensoramento remoto, Agricultura de precisão, AR Drone, Controle de altura, Planificador de rota.Resumo
Este artigo apresenta uma proposta para a coleta de informações sobre as culturas agrícolas utilizando um quadricóptero de baixo custo, chamado AR Drone 2.0. Para atingir o objetivo proposto foi desenhado um sistema de sensoriamento remoto que determina desafios, tais como a aquisição de fotografias aéreas de toda a colheita e a navegação do AR Drone em áreas não planas. O projeto está atualmente na sua fase de desenvolvimento. A primeira fase examina a plataforma e as ferramentas de hardware e de software necessárias para construir o protótipo proposto; a segunda fase descreve os experimentos de desempenho da estabilidade e da altura do AR Drone, a fim de conceber uma estratégia para o controle de altura em colheitas não planas; aliás, são avaliados algoritmos de planificação de rota com base na rota mais curta mediante grafos (Dijkstra, A *, e propagação da frente de onda) usando um quadricóptero simulado. A implementação dos algoritmos da rota mais curta é o início da cobertura total de uma colheita. Tanto as observações do comportamento do quadricóptero no simulador Gazebo, como os testes reais, demonstram a viabilidade de implementar o projeto usando o AR Drone como uma plataforma para um sistema de sensoriamento remoto para a agricultura de precisão.Referências
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Bongiovanni, R., & Lowenberg-Deboer, J. (2004). Precision agriculture and sustainability. Precision Agriculture, 5(4), 359-387.
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Chee, K., & Zhong, Z. (2013). Control, navigation and collision avoidance for an unmanned aerial vehicle. Sensors and Actuators A: Physical, 66-76.
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische mathematik, 1(1), 269-271.
Galceran, E., & Carreras, M. (2013). A survey on coverage path planning for robotics. Robotics and Autonomous Systems, 61(12), 1258-1276.
Gómez-Candón, D., De Castro, A., & López-Granados, F. (2014). Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat. Precision Agriculture, 5(1), 44-56.
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Guclu, A., & Arikan, K. B. (2012). Attitude and altitude control of an outdoor quadrotor [doctoral dissertation]. Atilim University: Ankara, Turkey.
Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. Systems Science and Cybernetics, IEEE Transactions on, 4(2), 100-107.
Jannoura, R., Brinkmann, K., Uteau, D., Bruns, C., & Joergensen, R. G. (2015). Monitoring of crop biomass using true colour aerial photographs taken from a remote controlled hexacopter. Biosystems Engineering, 129, 341-351.
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Li, J., & Li, Y. (2011). Dynamic analysis and PID control for a quadrotor. Mechatronics and Automation (ICMA), 2011 International Conference on (pp. 573-578). IEEE.
Mehranpour, M. R., Emamgholi, O., Shahri, A., & Farrokhi, M. (2013). A new fuzzy adaptive control for a Quadrotor flying robot. En Fuzzy Systems (IFSC), 2013 13th Iranian Conference on (págs. 1-5). IEEE.
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Primicerio, J., Di Gennaro, S. F., Fiorillo, E., Genesio, L., Lugato, E., Matese, A., & Vaccari, F. P. (2012). A flexible unmanned aerial vehicle for precision agriculture. Precision Agriculture, 13(4), 517-523.
Shengyi, Y., Kunqin, L., & Jiao, S. (2009). Design and simulation of the longitudinal autopilot of uav based on self-adaptive fuzzy pid control. In Computational Intelligence and Security, 2009. (pp. 634-638). IEEE.
Skiena, S. S. (1998). The algorithm design manual: Text. New york, NY: Springer Verlag.
Sugiura, R., Noguchi, N., & Ishii, K. (2005). Remote-sensing technology for vegetation monitoring using an unmanned helicopter. Biosystems Engineering, 90(4), 369-379.
Tailanian, M., Paternain, S., Rosa, R., & Canetti, R. (2014). Design and implementation of sensor data fusion for an autonomous quadrotor. In Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International (pp.1431-1436). IEEE.
Tanveer, M. H., Hazry, D., Warsi, F. A., & Joyo, M. K. (2013). Stabilized controller design for attitude and altitude controlling of quad-rotor under diisturbance and noisy conditios. American Journal of Applied Sciences, 10(8), 819-831.
Turner, D., Lucieer, A., & Watson, C. (2011). Development of an Unmanned Aerial Vehicle (UAV) for hyper resolution vineyard mapping based on visible, multispectral, and thermal imagery. En Proceedings of 34th International Symposium on Remote Sensing of Environment (pp.1-4). ISPRS. Retrieved from http://www.isprs.org/proceedings/2011/ISRSE-34/211104015Final00547.pdf
Valente, J. (2011). An aerial robotic framework to address area coverage in precision agriculture practices [doctoral dissetation]. Universidad Politécnica de Madrid: Spain.
ArduPilot autopilot suite (n.d.). APM Multiplataform Autopilot DRONECODE. (3DRobotics) Recuperado el 12 de Mayo de 2015, de http://ardupilot.com/
Arkin, R.C. (1990). Integrating behavioral, perceptual, and world knowledge in reactive navigation. Robotics and Autonomous Systems, 6(1), 105-122.
Bayar, V., Akar, B., Yayan, U., Yavuz, H. S., & Yazici, A. (2014). Fuzzy logic based design of classical behaviors for mobile robots in ROS middleware. In Innovations in Intelligent Systems and Applications (INISTA), Proceedings (pp.162-169). IEEE.
Bongiovanni, R., & Lowenberg-Deboer, J. (2004). Precision agriculture and sustainability. Precision Agriculture, 5(4), 359-387.
Bristeau, P. J., Callou, F., Vissiere, D., & Petit, N. (2011, August). The navigation and control technology inside the ar. drone micro uav. In Preprints of the 18th IFAC World Congress Milano (Italy) August 28 - September 2, 2011, (Vol. 18, No. 1, pp.1477-1484).
Chee, K., & Zhong, Z. (2013). Control, navigation and collision avoidance for an unmanned aerial vehicle. Sensors and Actuators A: Physical, 66-76.
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische mathematik, 1(1), 269-271.
Galceran, E., & Carreras, M. (2013). A survey on coverage path planning for robotics. Robotics and Autonomous Systems, 61(12), 1258-1276.
Gómez-Candón, D., De Castro, A., & López-Granados, F. (2014). Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat. Precision Agriculture, 5(1), 44-56.
Grenzdorffer, G., Engel, A., & Teichert, B. (2008). The photogrammetric potential of low-cost UAVs in forestry and agriculture. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 31(B3), 1207-1214.
Guclu, A., & Arikan, K. B. (2012). Attitude and altitude control of an outdoor quadrotor [doctoral dissertation]. Atilim University: Ankara, Turkey.
Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. Systems Science and Cybernetics, IEEE Transactions on, 4(2), 100-107.
Jannoura, R., Brinkmann, K., Uteau, D., Bruns, C., & Joergensen, R. G. (2015). Monitoring of crop biomass using true colour aerial photographs taken from a remote controlled hexacopter. Biosystems Engineering, 129, 341-351.
Jian-Guo, G., & Jun, Z. (2008). Altitude control system of autonomous airship based on fuzzy logic. In Systems and Control in Aerospace and Astronautics, 2008. (pp.1-5). IEEE.
Ji-hua, M., & Bing-fang, W. (2008). Study on the crop condition monitoring methods with remote sensing. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B8), 945-950.
Joseph, G. (2005). Fundamentals of remote sensing. Hyderabad, India: Universities Press.
Li, J., & Li, Y. (2011). Dynamic analysis and PID control for a quadrotor. Mechatronics and Automation (ICMA), 2011 International Conference on (pp. 573-578). IEEE.
Mehranpour, M. R., Emamgholi, O., Shahri, A., & Farrokhi, M. (2013). A new fuzzy adaptive control for a Quadrotor flying robot. En Fuzzy Systems (IFSC), 2013 13th Iranian Conference on (págs. 1-5). IEEE.
Meier, L., Camacho, J., Godbolt, B., Goppert, J., Heng, L., Lizarraga, M., ... & Tridgell, A. (2010). QGroundControl: Ground Control Station for Small Air-Land-Water Autonomous Unmanned Systems. Retrieved from: http://qgroundcontrol.org/
Pignon, P., & Choset, H. (1998). Coverage path planning: The boustrophedon cellular decomposition. In Field and Service Robotics (pp. 203-209). London, UK: Springer.
Primicerio, J., Di Gennaro, S. F., Fiorillo, E., Genesio, L., Lugato, E., Matese, A., & Vaccari, F. P. (2012). A flexible unmanned aerial vehicle for precision agriculture. Precision Agriculture, 13(4), 517-523.
Shengyi, Y., Kunqin, L., & Jiao, S. (2009). Design and simulation of the longitudinal autopilot of uav based on self-adaptive fuzzy pid control. In Computational Intelligence and Security, 2009. (pp. 634-638). IEEE.
Skiena, S. S. (1998). The algorithm design manual: Text. New york, NY: Springer Verlag.
Sugiura, R., Noguchi, N., & Ishii, K. (2005). Remote-sensing technology for vegetation monitoring using an unmanned helicopter. Biosystems Engineering, 90(4), 369-379.
Tailanian, M., Paternain, S., Rosa, R., & Canetti, R. (2014). Design and implementation of sensor data fusion for an autonomous quadrotor. In Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014 IEEE International (pp.1431-1436). IEEE.
Tanveer, M. H., Hazry, D., Warsi, F. A., & Joyo, M. K. (2013). Stabilized controller design for attitude and altitude controlling of quad-rotor under diisturbance and noisy conditios. American Journal of Applied Sciences, 10(8), 819-831.
Turner, D., Lucieer, A., & Watson, C. (2011). Development of an Unmanned Aerial Vehicle (UAV) for hyper resolution vineyard mapping based on visible, multispectral, and thermal imagery. En Proceedings of 34th International Symposium on Remote Sensing of Environment (pp.1-4). ISPRS. Retrieved from http://www.isprs.org/proceedings/2011/ISRSE-34/211104015Final00547.pdf
Valente, J. (2011). An aerial robotic framework to address area coverage in precision agriculture practices [doctoral dissetation]. Universidad Politécnica de Madrid: Spain.
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2015-09-30
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Esta publicação está licenciada sob os termos da licença CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.pt_BR).
