Visual servoing based trajectory tracking of underactuated water surface robots without direct position measurement

The trajectory tracking of underactuated water surface robots (or boats, surface vessels, etc.) has been an attractive topic over the past decade, and a lot of controllers are proposed for this challenging problem. However, most of the existing trajectory tracking controllers of the underactuated water surface robots assume the global positions of the robots can be accurately measured. In the working environments of the robots, the global position measurements are sometimes unstable or even unavailable. To avoid the direct position measurement, a new controller is proposed in this paper for the trajectory tracking of underactuated water surface robots by adopting the monocular visual feedback. This controller works on the basis of a novel adaptive algorithm for estimating global position of the robot online using visual feature tracking from a monocular camera, and its orientation and velocity measured by the AHRS (Attitude and Heading Reference System) sensor and visual odometry. It is proved by Lyapunov theory that the proposed adaptive visual servo controller gives rise to the asymptotic trajectory tracking and convergence of the position estimation to the actual position. An experiment is conducted to validate the effectiveness and robust performance of the proposed controller.