A Vision‐Guided Docking Method for Autonomous Underwater Vehicle From Ice Hole

ABSTRACT Reliable autonomous docking of AUV under ice is critical for operational safety, as maintaining vehicle integrity and achieving full‐lifecycle autonomous operations are unique challenges in ice hole recovery. This study presents a vision‐guided navigation framework specifically designed for ice hole docking, which enables accurate identification and localization of ice hole light beacons array. The framework integrates an adaptive selection algorithm that ensures robust light source detection across varying lighting conditions and operational distances, along with a dual‐quadrilateral geometry‐based recognition method capable of accurately discerning beacon positions in different visibility conditions during docking process. A monocular pose estimation algorithm provides real‐time and precise relative position and heading information, while an ice hole alignment strategy guides the AUV for safe and accurate docking. Images of six beacons arranged around the ice hole were captured by an upward‐facing camera mounted on the AUV and processed through the proposed pipeline. Extensive simulations and real‐world experiments demonstrate that the method significantly improves positioning accuracy, robustness, and overall navigation reliability, offering a practical and effective solution for underwater optical vision‐guided docking under ice.