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High-Speed Interception Multicopter Control by Image-based Visual Servoing

2024-04-12 07:40:26
Kun Yang, Chenggang Bai, Zhikun She, Quan Quan


In recent years, reports of illegal drones threatening public safety have increased. For the invasion of fully autonomous drones, traditional methods such as radio frequency interference and GPS shielding may fail. This paper proposes a scheme that uses an autonomous multicopter with a strapdown camera to intercept a maneuvering intruder UAV. The interceptor multicopter can autonomously detect and intercept intruders moving at high speed in the air. The strapdown camera avoids the complex mechanical structure of the electro-optical pod, making the interceptor multicopter compact. However, the coupling of the camera and multicopter motion makes interception tasks difficult. To solve this problem, an Image-Based Visual Servoing (IBVS) controller is proposed to make the interception fast and accurate. Then, in response to the time delay of sensor imaging and image processing relative to attitude changes in high-speed scenarios, a Delayed Kalman Filter (DKF) observer is generalized to predict the current image position and increase the update frequency. Finally, Hardware-in-the-Loop (HITL) simulations and outdoor flight experiments verify that this method has a high interception accuracy and success rate. In the flight experiments, a high-speed interception is achieved with a terminal speed of 20 m/s.

Abstract (translated)

近年来,关于无人机威胁公共安全报道增多。对于完全自主无人机入侵,传统方法如无线电干扰和GPS屏蔽可能失效。本文提出了一种使用带下摄像头的自主多旋翼拦截机动入侵者的计划。拦截器多旋翼可以自主检测并拦截高速飞行中的入侵者。带下相机避免了光电套件的复杂机械结构,使得拦截器多旋翼紧凑。然而,相机和多旋翼的运动耦合使得拦截任务困难。为了解决这个问题,基于图像的视觉伺服器(IBVS)控制器被提出,以实现快速和准确的拦截。然后,根据高速场景中传感器成像和图像处理的时间延迟,扩展了延迟卡尔曼滤波器(DKF)观察者,以预测当前图像位置并增加更新频率。最后,硬件在环(HITL)仿真和户外飞行实验证实了这种方法具有较高的拦截准确性和成功率。在飞行实验中,使用终端速度为20 m/s的高速拦截获得了成功。



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