Active Vision-Based Finite-Time Trajectory-Tracking Control of an Unmanned Surface Vehicle Without Direct Position Measurements

In this paper, a two-level visual servo strategy is elaborately devised for an unmanned surface vehicle (USV) equipped with a pan-tilt camera, so as to exactly track the desired trajectory around a visual target without direct position measurements. In the lower level, a barrier function-based adaptive pseudo-inverse (BFAP) controller is specially designed for the camera to keep the target in sight. Together with a finite-time position observer (FPO) and a finite-time extended state observer (FESO), a model-free finite-time trajectory-tracking control (MFTC) scheme is naturally synthesized for the USV on the higher level. Prominent advantages are presented as follows: 1) The BFAP controller can not only circumvent the singularity issue in a simpler manner, but also solve the field-of-view problem thoroughly in spite of unknown image depth; 2) The FPO provides a new vision-based method to locate the USV by rapidly calibrating a constant extrinsic parameter of the camera online, achieving higher positioning accuracy; and 3) The MFTC scheme allows all model information of the USV to be unknown, which is more favorable to practical implementations. Stability analyses are strictly made by the Lyapunov theory, and simulation studies conducted on the prototype CyberShip II comprehensively demonstrate remarkable performance of the proposed BFAP controller and MFTC scheme.