Image-Based Visual Servo Control for Ground Target Tracking Using a Fixed-Wing UAV with Pan-Tilt Camera

This paper proposes a control framework to achieve the tracking of the moving target by a fixed-wing unmanned aerial vehicle (UAV) with a monocular pan-tilt camera. This control framework is based on the image-based visual servoing (IBVS) method, which takes the target feature point on the captured image as the input and outputs the control signals directly with the aid of image Jacobian matrix. However, the image is affected by the attitude of both the UAV and the pan-tilt, and the attitude of the pan-tilt is coupled with that of the UAV simultaneously. To solve this problem, we present an "Ideal State" as the reference state, and make sure the coordinates of the feature point in the state are only affected by the change of the yaw angle of the UAV. In this way, we can integrate the attitude control of the UAV and the pan-tilt. By using this control framework, the fixed-wing UAV can track the ground target continuously on the one hand, and the target will tend to locate at image center on the other hand. This prevents the target from moving toward to the edge of the image or even disappearing. Besides, we prove the controller is exponentially convergent by the Lyapunov method. In order to evaluate the performance of our controller, we build a hardware-in-the-loop (HIL) simulation platform and a prototype platform. Based on these platforms, extensive experiments including simulations and real flight tests are conducted. The results show that our controller can achieve continuous and robust tracking of the target with a speed of 20km/h when the speed of the UAV is 16m/s.