Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter

Abstract: 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.