发表机构
Peking University（北京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出AMR-Pose框架，采用含红、蓝LED的标记模块，结合PSwPnP算法实现协作AUV的鲁棒相对位姿估计，经水池及闭环实验验证其准确性与实时性。
AI 中文摘要
协作自主水下航行器（AUV）之间的可靠相对位姿估计对协同海洋勘探、采样及多机器人协调至关重要。然而，水下环境中存在浊度、光照变化、反射及间歇性特征遮挡等严重光学退化问题，导致基于视觉的相对定位难以实现鲁棒性。本文提出AMR-Pose，一种用于协作AUV的基于主动LED标记的相对位姿估计框架。开发了一种紧凑的标记模块，包含1个红色中心LED和3个蓝色外围LED，集成于领航AUV上，可在复杂水下条件下提供独特视觉特征。基于检测到的标记观测，结合SE(3)上的李群位姿传播、概率标记关联及可见性自适应测量融合，提出概率切换透视-n-点估计器（PSwPnP），用于鲁棒六自由度相对位姿估计。该框架可根据标记可见性动态调整估计过程，在部分观测及可见性转换期间保持几何一致性和时间稳定性。通过带有运动捕捉真值的大量水池实验验证，AMR-Pose在挑战性水下条件下实现了准确、平滑且鲁棒的相对位姿估计；闭环领航-跟随实验进一步证明其适用于协作水下机器人的实时相对位姿反馈。
英文摘要
Reliable relative pose estimation between autonomous underwater vehicles (AUVs) is critical for cooperative ocean exploration, sampling, and multi-robot coordination. However, achieving robust vision-based relative localization in underwater environments remains challenging due to severe optical degradation, including turbidity, illumination variations, reflections, and intermittent feature occlusions. This paper presents AMR-Pose, an active LED marker-based relative pose estimation framework for cooperative AUVs. A compact marker module consisting of one red central LED and three blue peripheral LEDs is developed and integrated onto the leader AUV to provide distinctive visual features under complex underwater conditions. Building upon the detected marker observations, a probabilistic switching Perspective-n-Point estimator (PSwPnP) is developed by combining Lie-group pose propagation on $SE(3)$, probabilistic marker association, and visibility-adaptive measurement fusion for robust six-degree-of-freedom relative pose estimation. The proposed framework dynamically adapts the estimation process according to marker visibility, maintaining geometric consistency and temporal stability during partial observations and visibility transitions. Extensive water-tank experiments with motion-capture ground truth validate that AMR-Pose achieves accurate, smooth, and robust relative pose estimation under challenging underwater conditions. Closed-loop leader-follower experiments further demonstrate its feasibility for real-time relative pose feedback in cooperative underwater robotics.
