An Optimized Image-Based Visual Servo Control for Fixed-Wing Unmanned Aerial Vehicle Target Tracking With Fixed Camera

This paper presents an optimized image-based visual servo (IBVS) control scheme for tracking a ground target by using a fixed-wing unmanned aerial vehicle (UAV) with a monocular camera fixed on it. Unlike the widely used rotor UAVs, the fixed-wing UAV has much more dynamical constraints such as it cannot move omni-direction and its minimum speed is limited by the stalling speed. This makes the target tracking problem more challenging. The proposed scheme leverages the image Jacobian matrix to build a connection between the velocity of the feature point and that of the UAV. Afterward, considering the camera is fixed on the body of the UAV, an “ideal camera” model is proposed to compensate the shifts of the feature point caused by the changes of the UAV's attitude. Then, an optimized control law without solving the pseudo-inverse of the image Jacobian matrix is proposed with the aid of the least square method from the target center in the image coordinate system. This control law takes the velocity of the feature point as inputs and the yaw angular velocity of the UAV as outputs. The stability of the proposed law is analyzed with the Lyapunov method, showing that the UAV will circle around the ground target asymptotically. Finally, the proposed scheme is evaluated by a hardware-in-the-loop (HIL) simulation based on the Gazebo simulator and the off-the-shelf autopilot hardware.