Robust Vision-Based Control of a Rotorcraft UAV for Uncooperative Target Tracking

This paper investigates the problem of using an unmanned aerial vehicle (UAV) to track and hover above an uncooperative target, such as an unvisited area or an object that is newly discovered. A vision-based strategy integrating the metrology and the control is employed to achieve target tracking and hovering observation. First, by introducing a virtual camera frame, the reprojected image features can change independently of the rotational motion of the vehicle. The image centroid and an optimal observation area on the virtual image plane are exploited to regulate the relative horizontal and vertical distance. Then, the optic flow and gyro measurements are utilized to estimate the relative UAV-to-target velocity. Further, a gain-switching proportional-derivative (PD) control scheme is proposed to compensate for the external interference and model uncertainties. The closed-loop system is proven to be exponentially stable, based on the Lyapunov method. Finally, simulation results are presented to demonstrate the effectiveness of the proposed vision-based strategy in both hovering and tracking scenarios.