Wang Liang, Ai JianLiang, Zhang Li, Xing Zhenlin
Department of Aeronautics and Astronautics, Fudan University, Shanghai 200433, China.
Sensors (Basel). 2020 Apr 27;20(9):2475. doi: 10.3390/s20092475.
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.
近年来，机场和机场跑道上报的无人机与飞机之间的事故数量不断上升。提出了一种基于计算机视觉的机场净空区监测无人机系统设计方案。该系统集成了识别、跟踪和驱赶功能，主要用于低成本控制气球类空中物体和小型飞机。首先，分析了四旋翼动力学模型和二自由度云台模型，并设计了基于干扰补偿的姿态反步控制器。其次，针对复杂环境构建了低空慢速小目标自识别与跟踪技术。基于你只看一次（YOLO）和内核相关滤波器（KCF）算法，设计了一种具有高鲁棒性和高可靠性的自主目标识别与高速跟踪方案。第三，设计了基于抗饱和比例积分微分（PID）算法的云台控制器和自动瞄准策略，并制造了一种简化的、具有高速高精度特点的自动瞄准驱赶装置——环保凝胶球发射器。通过原型实验可以验证该方案的可行性和稳定性。
