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.
@article{arxiv.2409.17497,
title = {Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter},
author = {Hailong Yan and Kun Yang and Yixiao Cheng and Zihao Wang and Dawei Li},
journal= {arXiv preprint arXiv:2409.17497},
year = {2025}
}
Comments
11 pages, 17 figures, has been accepted by the Journal of IEEE Transactions on Industrial Electronics