Monocular visual servo-based stabilization control of underactuated unmanned surface vehicle

Aiming at the accurate posture stabilization problem of an under-actuated unmanned surface vehicle (USV) in GPS-denied environments, a monocular visual servo stabilization control scheme is proposed based on homography.

By virtue of the homography decomposition technique, posture errors with an unknown scale factor are directly reconstructed from current and desired images, which thoroughly removes the calibration of extrinsic camera parameters and priori information on visual targets; with respect to the under-actuation constraint, a periodic function to persistently excite the yaw angle is incorporated into the continuous time-variant output feedback controller, allowing the USV to be stabilized in the absence of image depth, movement velocities and model parameters.

Under the framework of the Lyapunov theory, the closed-loop visual servo system of the USV is rigorously proven to be asymptotically stable by Barbalat lemma.

By installing an onboard monocular camera, USV posture errors can be precisely stabilized with the aid of the proposed visual servo strategy, providing significant technique support for practical applications including docking, berthing, dynamic positioning, etc.