Hierarchical Model Predictive Image-Based Visual Servoing of Underwater Vehicles With Adaptive Neural Network Dynamic Control.

This paper proposes a hierarchical image-based visual servoing (IBVS) strategy for dynamic positioning of a fully actuated underwater vehicle. In the kinematic loop, the desired velocity is generated by a nonlinear model predictive controller, which optimizes a cost function of the predicted image trajectories under the constraints of visibility and velocity. A velocity reference model, representing the desired closed-loop vehicle dynamics, is integrated with an IBVS kinematic model to predict the future trajectories.