Design and Implementation of Underwater Robotic Systems for Visual–Inertial Trajectory Estimation and Robust Motion Control

Reliable trajectory estimation and precise motion control are the prerequisites for underwater robotic systems to perform complex autonomous tasks, which are essential for enhancing the operational efficiency of intelligent underwater facilities. However, the inherent asymmetry of underwater hydrodynamics, featureless images caused by complex environments, and the lack of high-frequency state feedback significantly hinder stable trajectory tracking and robust autonomous navigation. To address these challenges, this paper proposes an integrated autonomous navigation and robust control scheme for underwater robotic systems. Specifically, we first propose a visual–inertial trajectory estimation method for underwater robotic systems, which effectively overcomes the challenges of featureless images and provides consistent, real-time pose feedback for motion execution. Furthermore, we develop a hierarchical robust motion control strategy for autonomous underwater robots, which integrates model predictive control with incremental nonlinear dynamic inversion to achieve precise positioning performance and reliable operation under environmental disturbances. Finally, we design and implement a customized, highly integrated underwater robotic platform that integrates the proposed trajectory estimation and robust control modules, with its performance validated through extensive field experiments in underwater scenarios. The experimental results demonstrate that the proposed system can effectively achieve high-precision trajectory tracking and maintain operational stability, providing a comprehensive engineering solution for the autonomous navigation of underwater robots in complex environments.