Hierarchical Planning and Control for Underwater Dynamic Docking Based on Model Predictive Optimization

Abstract

This paper addresses the dynamic docking problem of Unmanned Underwater Vehicles (UUVs). A hierarchical planning and control framework with a unified prediction horizon is proposed based on model predictive optimization. A Dynamic Window Approach (DWA) algorithm is employed in the high-level planning layer to generate reference trajectories that consider the relative motion and dynamic constraints between the UUV and the recovery target. A Nonlinear Model Predictive Control (NMPC) scheme is formulated at the low-level control layer to track planned trajectories by solving a constrained nonlinear optimization problem. To improve computational efficiency, warm-start initialization and a receding horizon strategy are integrated into the control framework. Simulation results demonstrate that the proposed method significantly improves docking accuracy under complex ocean currents.