Research on Aerial Autonomous Docking and Landing Technology of Dual Multi-Rotor UAV.

This paper studies the cooperative control of multiple unmanned aerial vehicles (UAVs) with sensors and autonomous flight capabilities. In this paper, an architecture is proposed that takes a small quadrotor as a mission UAV and a large six-rotor as a platform UAV to provide an aerial take-off and landing platform and transport carrier for the mission UAV. The design of a tracking controller for an autonomous docking and landing trajectory system is the focus of this research. To examine the system's overall design, a dual-machine trajectory-tracking control simulation platform is created via MATLAB/Simulink. Then, an autonomous docking and landing trajectory-tracking controller based on radial basis function proportional-integral-derivative control is designed, which fulfills the trajectory-tracking control requirements of the autonomous docking and landing process by efficiently suppressing the external airflow disturbance according to the simulation results. A YOLOv3-based vision pilot system is designed to calibrate the rate of the aerial docking and landing position to eight frames per second. The feasibility of the multi-rotor aerial autonomous docking and landing technology is verified using prototype flight tests during the day and at night. It lays a technical foundation for UAV transportation, autonomous take-off, landing in the air, and collaborative networking. In addition, compared with the existing technologies, our research completes the closed loop of the technical process through modeling, algorithm design and testing, virtual simulation verification, prototype manufacturing, and flight test, which have better realizability.

Design of Airport Obstacle-Free Zone Monitoring UAV System Based on Computer Vision.

In recent years, a rising number of incidents between Unmanned Aerial Vehicles (UAVs) and planes have been reported at airports and airfields. A design scheme for an airport obstacle-free zone monitoring UAV system based on computer vision is proposed. The system integrates the functions of identification, tracking, and expelling and is mainly used for low-cost control of balloon airborne objects and small aircrafts. First, a quadcopter dynamic model and 2-Degrees of Freedom (2-DOF) Pan/Tilt/Zoom (PTZ) model are analyzed, and an attitude back-stepping controller based on disturbance compensation is designed. Second, a low and slow small-target self-identification and tracking technology is constructed against a complex environment. Based on the You Only Look Once (YOLO) and Kernel Correlation Filter (KCF) algorithms, an autonomous target recognition and high-speed tracking plan with great robustness and high reliability is designed. Third, a PTZ controller and automatic aiming strategy based on Anti-Windup Proportional Integral Derivative (PID) algorithm is designed, and a simplified, automatic-aiming expelling device, the environmentally friendly gel ball blaster, which features high speed and high accuracy, is built. The feasibility and stability of the project can be verified through prototype experiments.