Image-Based Visual Servoing of a Quadrotor with Improved Visibility Using Model Predictive Control

Abstract

In this paper, an observer-based model predictive control scheme is proposed for the image-based visual servoing (IBVS) of a quadrotor. The control objective is to regulate the relative pose of the quadrotor to a planar ground target using a minimal sensor set, i.e., a monocular camera and an inertia measurement unit (IMU). Image features are deliberately selected to decouple the roll/pitch motion from the image kinematics, such that the overall system dynamics possesses a cascaded structure. This structural property enables the simplification of the controller design by adopting a dual-loop control structure. During visual servoing, the target object could potentially leave the field of view (FOV) of the camera, which causes failure of control input generation. To improve the visibility, a model predictive control (MPC) controller is developed to explicitly bound the roll and pitch angles to alleviate the feature loss due to large rotation. In addition, a high-gain observer is designed to facilitate the estimation of the linear velocity, which is unavailable due to the absence of the global positioning system (GPS). In the end, simulation results are presented to verify the effectiveness of the proposed control scheme.