Autonomous landing process can be triggered and override at any time using remote controller. This technique takes very small execution time for data processing in fuzzy logic, which is essential for high-speed data processing and updating. The lookup table technique is used to implement fuzzy logic inside Arduino Mega. This paper includes a landing system based on laser rangefinder, Arduino Mega MCU, and Pixhawk flight controller. Therefore, a fuzzy logic-based safe landing system is proposed in this paper. It needs a lot of practice and effort for a safe landing. Quadcopter landing is most crucial part of the overall operating process. Quadcopter configuration of UAV is most common due to its simplicity, stability, and versatile controllability. Published by AIP Publishing.Recent years, unmanned aerial vehicles (UAVs) have been used to perform various tasks such as surveillance, monitoring, rescue, photography, and security. Matsuura, “ Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance,” Climate Research 30, 79– 82 (2005). Ben Atitallah, “ Quadcopter Trajectory Tracking and Attitude Control Based on Euler Angle Limitation,” in 2018 6th International Conference on Control Engineering & Information Technology (CEIT) ( IEEE, Istanbul, Turkey, 2018) pp. Pasdar, “ A hybrid fuzzy approach for landing of a quad-rotor MAV based on a novel vision localization method,” in 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM) ( IEEE, Tehran, Iran, 2015) pp. Mu, “ Vision-guided autonomous landing of multirotor UAV on fixed landing marker,” in 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) (IEEE, Dalian, China, 2020) pp. Lee, “ Robust marker tracking algorithm for precise UAV vision-based autonomous landing,” in 2015 15th International Conference on Control, Automation and Systems (ICCAS) ( IEEE, Busan, Korea (South), 2015) pp. Zhong, “ HArCo: Hierarchical Fiducial Markers for Pose Estimation in Helicopter Landing Tasks,” in 2015 IEEE International Conference on Systems, Man, and Cybernetics ( IEEE, Kowloon Tong, Hong Kong, 2015) pp. Manzoni, “ A vision-based system for autonomous vertical landing of unmanned aerial vehicles,” in 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT) (2019) pp. Medina-Carnicer, “ Generation of fiducial marker dictionaries using Mixed Integer Linear Programming,” Pattern Recognition 51 (2015). Medina-Carnicer, “ Speeded Up Detection of Squared Fiducial Markers,” Image and Vision Computing 76 (2018). Stopforth, “ Autonomous Landing of a Multirotor Aircraft on a Docking Station,” in 2020 International SAUPEC/RobMech/PRASA Conference (2020) pp. Medina-Carnicer, “ Fractal Markers: A New Approach for Long-Range Marker Pose Estimation Under Occlusion,” IEEE Access 7, 169908– 169919 (2019). Tanaka, “ Study on accuracy improvement under bad condition in GPS,” in SICE 2004 Annual Conference, Vol. Pfeucil, “ Cooperative µUAV-UGV autonomous indoor surveillance,” in International Multi-Conference on Systems, Signals Devices (2012) pp. Shamma, “ Chapter 14 - RISCuer: A reliable multi-UAV search and rescue testbed,” in Unmanned Aerial Systems, Advances in Nonlinear Dynamics and Chaos (ANDC), edited by A. Quagliotti, “ Monitoring performances and cost estimation of multirotor Unmanned Aerial Systems in precision farming,” in 2015 International Conference on Unmanned Aircraft Systems (ICUAS) (2015) pp. Furthermore, the landing trajectory and landing time are analyzed to understand the tradeoffs between the two tested methods. The test results show that the proposed method reduces the landing positional error by 88.3% compared to a non-camera landing while showing a high level of reliability. This computer also acts as a high-level processor to control the quadcopter during the landing by using a simple velocity-limited proportional control to set its velocity on horizontal axes and a fixed setpoint velocity for the vertical axis. The marker can be detected by the onboard camera, which allows for a six-degree-of-freedom (DOF) pose estimation by utilizing the onboard computer. In this study, Fractal Marker was added as a visual target to improve the localization accuracy of the multirotor during the landing. Multirotor landing systems relying on GPS/INS navigation alone have insufficient accuracy due to the change of geometry of the transmitting satellite or object obstruction to the GPS receiver.
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