Robust image-based control of the quadrotor unmanned aerial vehicle

This paper proposes an image-based visual servo controller for the quadrotor vertical takeoff and landing unmanned aerial vehicle (UAV). The controller utilizes an estimate of flow of image features as the linear velocity cue and assumes angular velocity and attitude information available for feedback. The image features are selected from perspective image moments and projected on a suitably defined image plane, providing decoupled kinematics for the translational motion. A nonlinear observer is designed to estimate the flow of image features using outputs of visual information. The controller for the translational dynamics is bounded which helps to keep the target points in the field of view of the camera. A smooth asymptotic controller, using the robust integral of the sign of the error method, is designed for the rotational dynamics in order to compensate for the unmodeled dynamics and external disturbances. Furthermore, the proposed approach is robust with respect to unknown image depth through an adaptive scheme and also the yaw information of the UAV is not required. The complete Lyapunov-based stability analysis is presented to show that all states of the system are bounded and the error signals converge to zero. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.