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

TL;DR

This paper presents a novel image-based visual servoing method combined with guidance algorithms for precise interception of targets by multicopters, achieving high accuracy and success rates in simulations and real-world tests.

Contribution

It introduces an integrated IBVS and PNG approach with a DKF for improved accuracy and stability in multicopter interception tasks, addressing camera-motion coupling and evasive targets.

Findings

CEP of 0.089 m in simulations

Over 80% interception success in real-world tests

Reduced multicopter overload during interception

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.