Autonomous Landing of UAV Based on Artificial Neural Network Supervised by Fuzzy Logic

Abu-Jbara, K., Alheadary, W., Sundaramorthi, G., & Claudel, C. (2015). A robust vision-based runway detection and tracking algorithm for automatic UAV landing. In 2015 International conference on unmanned aircraft systems (ICUAS) (pp. 1148–1157). IEEE.

Amazon.com. Amazon prime air. (2015). http://www.amazon.com/b?node=8037720011 .

Benavidez, P., Lambert, J., Jaimes, A., & Jamshidi, M. (2014). Landing of an ardrone 2.0 quadcopter on a mobile base using fuzzy logic. In World Automation Congress (WAC), 2014 (pp. 803–812). IEEE.

Carvalho, J. P., Jucá, M., Menezes, A., Olivi, L., Bessa, A., & Marcato, A. (2016). Landing an UAV in a dynamical target using fuzzy control and computer vision. In Congresso Brasileiro de Automática (CBA), 2016.

Carvalho, J. P., Jucá, M., Menezes, A., Olivi, L., Bessa, A., & Marcato, A. (2017). Lecture notes in electrical engineering, chapter Autonomous UAV outdoor flight controlled by an embedded system using Odroid and ROS, (402 ed, pp. 423–437). Springer.

Cocchioni, F., Pierfelice, V., Benini, A., Mancini, A., Frontoni, E., Zingaretti, P., Ippoliti, G., & Longhi, S. (2014). Unmanned ground and aerial vehicles in extended range indoor and outdoor missions. In 2014 International conference on unmanned aircraft systems (ICUAS) (pp. 374–382). IEEE.

Delgado, F. S., Carvalho, J. P., Coelho, T. V. N., & Dos Santos, A. B. (2016). An optical fiber sensor and its application in UAVs for current measurements. Sensors, 16(11), 1800.

Freire, F. P., Martins, N. A., & Splendor, F. (2018). A simple optimization method for tuning the gains of PID controllers for the autopilot of cessna 182 aircraft using model-in-the-loop platform. Journal of Control, Automation and Electrical Systems, 29, 1–10.

Gautam, A., Sujit, P., & Saripalli, S. (2014). A survey of autonomous landing techniques for UAVs. In 2014 International conference on unmanned aircraft systems (ICUAS), (pp. 1210–1218). IEEE.

Gui, Y., Guo, P., Zhang, H., Lei, Z., Zhou, X., Du, J., et al. (2013). Airborne vision-based navigation method for UAV accuracy landing using infrared lamps. Journal of Intelligent and Robotic Systems, 72(2), 197–218.

Guo, X., Denman, S., Fookes, C., Mejias, L., & Sridharan, S. (Nov 2014) Automatic UAV forced landing site detection using machine learning. In 2014 International conference on digital lmage computing: Techniques and applications (DlCTA) (pp. 1–7). https://doi.org/10.1109/DICTA.2014.7008097 .

HardKernel. Odroid. (2015). http://www.hardkernel.com/ . Accessed 1 Aug 2018.

Karuppanan, P., & Mahapatra, K. K. (2012). PI and fuzzy logic controllers for shunt active power filtera report. ISA Transactions, 51(1), 163–169.

Kim, J., Jung, Y., Lee, D., & Shim, D. H. (2016). Landing control on a mobile platform for multi-copters using an omnidirectional image sensor. Journal of Intelligent & Robotic Systems, 84(1–4), 529–541.

Lee, D., Ryan, T., & Kim, H. J. (2012). Autonomous landing of a vtol UAV on a moving platform using image-based visual servoing. In 2012 IEEE international conference on robotics and automation (ICRA) (pp. 971–976). IEEE.

Lee, H., Jung, S., & Shim, D. H. (2016). Vision-based UAV landing on the moving vehicle. In 2016 International conference on unmanned aircraft systems (ICUAS) (pp. 1–7). IEEE.

Ma, Z., Wang, C., Niu, Y., Wang, X., & Shen, L. (2018). A saliency-based reinforcement learning approach for a UAV to avoid flying obstacles. Robotics and Autonomous Systems, 100, 108–118.

Maravall, D., de Lope, J., & Fuentes, J. P. (2015). Vision-based anticipatory controller for the autonomous navigation of an UAV using artificial neural networks. Neurocomputing, 151, 101–107.

Meier, L., Honegger, D., & Pollefeys, M. (2015). Px4: A node-based multithreaded open source robotics framework for deeply embedded platforms. In 2015 IEEE international conference on robotics and automation (ICRA) (pp. 6235–6240). https://doi.org/10.1109/ICRA.2015.7140074 .

Meier, L., Tanskanen, P., Fraundorfer, F., & Pollefeys, M. (2011). The pixhawk open-source computer vision framework for mavs. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(1), C22.

Moore, D. (2007). The basic practice of statistics. New York: W.H. Freeman. ISBN 9780716774631.

Nex, F., & Remondino, F. (2014). Uav for 3d mapping applications: A review. Applied Geomatics, 6(1), 1–15.

Olivares-Mendez, M. A., Kannan, S., & Voos, H. (2015). Vision based fuzzy control autonomous landing with UAVs: From v-rep to real experiments. In 2015 23th Mediterranean conference on control and automation (MED) (pp. 14–21). IEEE.

Pereira, G. A. S., Resende, G. D., & Gonçalves, V. M. (2018). Pouso de veículos aéreos utilizando campos vetoriais e visãocomputacional [Landing of aircraft using vector fields and computervision]. In XXII Congresso Brasileiro de Automatica. SBA.

Precup, R.-E., & Hellendoorn, H. (2011). A survey on industrial applications of fuzzy control. Computers in Industry, 62(3), 213–226.

QGroundControl. Mavlink. (2016). http://qgroundcontrol.org/mavlink/start . Accessed 1 Aug 2018.

Rathinam, S., Almeida, P., Kim, Z., Jackson, S., Tinka, A., Grossman, W., & Sengupta, R. (2007). Autonomous searching and tracking of a river using an uav. In American control conference, 2007. ACC’07 (pp. 359–364). IEEE.

ROS. Robot operating system. (2015). www.ros.org/ . Accessed 1 Aug 2018.

Saska, M., Krajnik, T., & Pfeucil, L. (2012). Cooperative micro-UAV-UGV autonomous indoor surveillance. In International multi-conference on systems, signals and devices (pp. 1–6).

Silva, N. B., Fontes, J. V., Inoue, R. S., & Branco, K. R. (2018). Dynamic inversion and gain-scheduling control for an autonomous aerial vehicle with multiple flight stages. Journal of Control, Automation and Electrical Systems, 29(3), 328–339.

Theodoridis, S., & Koutroumbas, K. (2008). Pattern recognition (4th ed.). Cambridge: Academic Press. ISBN 1597492728, 9781597492720.

Tyagi, K., & Sharma, A. (2014). An adaptive neuro fuzzy model for estimating the reliability of component-based software systems. Applied Computing and Informatics, 10(1–2), 38–51.

Wang, X. (2013). Takeoff/landing control based on acceleration measurements for vtol aircraft. Journal of the Franklin Institute, 350(10), 3045–3063.

Wenzel, K. E., Masselli, A., & Zell, A. (2011). Automatic take off, tracking and landing of a miniature uav on a moving carrier vehicle. Journal of Intelligent and Robotic Systems, 61, 221–238.

Yang, S., Ying, J., Lu, Y., & Li, Z. (2015). Precise quadrotor autonomous landing with srukf vision perception. In 2015 IEEE international conference on robotics and automation (ICRA) (pp. 2196–2201). IEEE.