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.

This study proposes an aerial recovery technology that can complete aerial recovery for target unmanned aerial vehicles (UAVs) by a platform UAV to overcome the limitation of ground recovery for multirotor UAVs. To ensure the safety of automatic aerial recovery, more requirements are made for the stability of multi-rotor UAVs. This study proposes a back-stepping trajectory tracking controller for feedforward compensation of uncertain disturbances. The results of the simulation show that the controller can effectively prevent external disturbance and meet requirements for the desired trajectory tracking. Furthermore, based on a you only look once (YOLO) network, this study designs a real-time image recognition and positioning system, which can achieve real-time positioning for platform UAV by the target UAV with an image-processing rate of 8 frames per second (FPS). With the main objective of safety, this study designs an automatic recovery guiding system for target UAVs using a fuzzy controller. The target UAVs can automatically realize a soft landing on the platform UAV effect of the guiding system. Finally, this study conducts dynamic recovery tests inflight and verifies the feasibility of automatic aerial recovery technology for multi-rotor UAVs.

No abstract

No abstract