Preliminary Online Validation of a Visual-Acoustic-based Framework for Autonomous Underwater Structure Inspections

This paper presents the preliminary experimental validation of a visual-acoustic-based framework for the autonomous inspection of critical underwater infrastructures using Autonomous Underwater Vehicles (AUVs). The goal is to evaluate the feasibility of a strategy that enables an AUV to navigate relative to a target while maintaining a desired configuration. The proposed target relative navigation approach employs a minimal sensor suite - comprising a frontal stereo camera, a frontal acoustic range sensor, and an inertial unit - to provide information on the relative orientation and distance of the AUV from the inspection surface. This information is used to compute control actions that allow the vehicle to dynamically adjust its pose relative to the facility, adhering to specific mission requirements. The system was validated through an at-sea experimental campaign, during which a reference AUV performed relative navigation tests in front of a port dock. During the experiments, the target relative navigation solution was integrated into the robot software architecture to provide online feedback, thus enabling the AUV to maintain the desired distance and orientation relative to the dock. The results demonstrate the effectiveness and robustness of the proposed relative navigation approach, confirming its feasibility for enhancing the autonomous capabilities of underwater robots in marine infrastructure inspection tasks. Even under deliberate perturbations introduced via joystick by an operator, the AUV successfully maintained a reference distance from the harbor quay and regulated its orientation to zero, ensuring the frontal perception payload remained aligned with the target.