LAUSR

In this article, in the presence of completely unknown dynamics and unmeasurable velocities, a dynamics-level finite-time fuzzy monocular visual servo (DFFMVS) scheme is created for regulating an unmanned surface vehicle (USV) to the desired pose. Main contributions are as follows: first, with the aid of homography decomposition, a novel homography-based visual servo structure for a USV with both kinematics and dynamics is first established such that complex unknowns including unmeasurable poses and velocities, image depth, system dynamics, and time-varying inertia are sufficiently encapsulated; second, using finite-time observer technique, finite-time velocity observer (FVO) based visual-servo error dynamics are elaboratively formulated, and thereby facilitating backstepping synthesis; third, by virtue of the FVO, the adaptive fuzzy dynamics approximator together with adaptive residual feedback is deployed to compensate complex unknowns, and thereby contributing to accurate regulation of pose errors; and fourth, a completely model-free monocular visual servo approach only using a camera is eventually invented. Simulation studies on a benchmark prototype USV demonstrate that the proposed DFFMVS scheme has remarkable performance with significant superiority in both visual servo and unknowns observation.