Adaptive Visual Servoing of Unmanned Aerial Vehicles in GPS-Denied Environments

This paper presents an adaptive output feed back-based visual servoing law for a quadrotor unmanned aerial vehicle equipped with a single downward facing camera. The objective is to regulate the relative position and yaw of the vehicle to a planar target consisting of multiple points using a minimal sensor set, i.e., an inertial measurement unit and a vision sensor. A set of first order image moment features, defined in the image plane of a virtual camera with zero roll and pitch motion, is used for visual servoing. It has been observed in previous work that various system uncertainties, such as aerodynamics constants and attitude estimation bias, result in steady-state errors if not being compensated. By treating those uncertainties as unknown system parameters, an adaptive backstepping controller is developed. As the given visual servoing law is an output feedback controller, the translational velocity measurement from the global position system is not required. The asymptotic stability of the error dynamics is proven. Experimental results are provided to demonstrate the controller performance.