Vision-Based Tracking Control of Underactuated Water Surface Robots Without Direct Position Measurement

Over the past decade, the trajectory tracking of underactuated water surface robots (or boats, surface vessels, etc.) has been an attractive topic in the control and automation community, and numerous controllers are proposed for this challenging problem. However, most, if not all, 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 practical applications, the global position measurement systems are sometimes unstable or even unavailable in the working environments of the robots. To avoid the direct position measurement, this brief presents a new controller for the trajectory tracking of underactuated water surface robots using 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 attitude and heading reference system sensor and a velocity observer. It is proved by Lyapunov theory that the proposed adaptive visual servo controller gives rise to asymptotic tracking of a desired trajectory and convergence of the position estimation to the actual position. Experiments are conducted to validate the effectiveness and robust performance of the proposed controller.