用视觉伺服+比例导引，让无人机精准拦截移动目标。
Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter
- 结合视觉伺服与比例导引，降低拦截阶段过载。
- 仿真中误差仅0.089米，比之前方法低72.8%。
- 适合低空非合作目标的高精度实时拦截场景。
搭载固定相机的多旋翼无人机进行基于视觉的拦截面临相机运动耦合与目标规避的挑战。本文提出一种融合图像基视觉伺服（IBVS）与比例导航导引（PNG）的方法，在拦截末段降低无人机过载。通过将IBVS控制器生成的平滑轨迹与延迟卡尔曼滤波器（DKF）实现的高频目标二维位置估计相结合，有效缓解图像处理延迟对精度的影响。同时设计视场保持控制器以保障视觉伺服系统稳定性。实验结果表明，仿真中圆概率误差（CEP）达0.089米（较最新相关IBVS工作降低72.8%），真实环境下风速低于4米/秒时拦截成功率超80%。结果验证了该系统在精确低空拦截非合作目标方面的潜力。
原文摘要 · Abstract (English)
Vision-based interception using multicopters equipped strapdown camera is challenging due to camera-motion coupling and evasive targets. This paper proposes a method integrating Image-Based Visual Servoing (IBVS) with proportional navigation guidance (PNG), reducing the multicopter's overload in the final interception phase. It combines smoother trajectories from the IBVS controller with high-frequency target 2D position estimation via a delayed Kalman filter (DKF) to minimize the impact of image processing delays on accuracy. In addition, a field-of-view (FOV) holding controller is designed for stability of the visual servo system. Experimental results show a circular error probability (CEP) of 0.089 m (72.8% lower than the latest relevant IBVS work) in simulations and over 80\% interception success under wind conditions below 4 m/s in real world. These results demonstrate the system's potential for precise low-altitude interception of non-cooperative targets.
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