Image-based finite-time visual servoing of a quadrotor for tracking a moving target

Abstract

This paper proposes an image-based visual servoing control method for a moving target of a quadrotor UAV (QUAV). Firstly, the dynamic image model with moving target parameters is established based on the image moment features in the virtual camera plane. For the unpredictability of the moving target in space, we use a high-order differentiator to estimate the state parameters of the moving target. In order to solve the problem of image depth information caused by a monocular camera, we derive a nonlinear finite-time linear velocity observer from the virtual image plane, which can not only estimate the linear velocity information of QUAV but also avoid the measurement of image depth. Based on the above information, we design the global finite-time controller and use Lyapunov theory to prove the finite-time stability of the system. Finally, the numerical simulations verify the convergence of the proposed control scheme, and the ROS gazebo simulations demonstrate the improved performance of the proposed control scheme in tracking error.