用于驻留水下车辆的对接与持久操作
Docking and Persistent Operations for a Resident Underwater Vehicle
AI总结：
本文提出了一种驻留水下车辆系统，通过水下机器人自主导航和对接，实现了持久无人操作，验证了水声与视觉导航在真实环境中的可行性。
摘要：
对流体动力学的理解仍然受限于稀疏和不频繁的观测，主要因为当前方法受制于水下监测的高成本和后勤努力，依赖于在广阔区域进行零散调查或在固定位置进行长期测量。为克服这些限制，监控系统必须能够实现持久和自主的操作，而无需持续的水面支持。尽管近年来取得了进展，但驻留水下车辆仍然罕见，由于自主性、机器人韧性以及机械坚固性方面的持续挑战，特别是在长期部署在恶劣和偏远环境中的情况。本文通过展示使用90米深度的对接站和小型遥控潜水器（ROV）的驻留基础设施的开发、部署和操作，解决了这些问题。ROV配备了增强的 onboard 处理和感知能力，使其能够使用USBL信号自主导航，通过结合扩展卡尔曼滤波器的ArUco标记基于视觉局部化进行对接，并执行局部检查任务。该系统实现了90%的自主对接成功率，并在四分钟内完成了完整的检查任务，验证了在真实环境中声学和视觉导航的整合。这些结果表明，深度处可靠、无缆操作是可行的，突显了驻留ROV系统在可扩展、低成本水下监测方面的潜力。
英文摘要：
Our understanding of the oceans remains limited by sparse and infrequent observations, primarily because current methods are constrained by the high cost and logistical effort of underwater monitoring, relying either on sporadic surveys across broad areas or on long-term measurements at fixed locations. To overcome these limitations, monitoring systems must enable persistent and autonomous operations without the need for continuous surface support. Despite recent advances, resident underwater vehicles remain uncommon due to persistent challenges in autonomy, robotic resilience, and mechanical robustness, particularly under long-term deployment in harsh and remote environments. This work addresses these problems by presenting the development, deployment, and operation of a resident infrastructure using a docking station with a mini-class Remotely Operated Vehicle (ROV) at 90 m depth. The ROV is equipped with enhanced onboard processing and perception, allowing it to autonomously navigate using USBL signals, dock via ArUco marker-based visual localisation fused through an Extended Kalman Filter, and carry out local inspection routines. The system demonstrated a 90 % autonomous docking success rate and completed full inspection missions within four minutes, validating the integration of acoustic and visual navigation in real-world conditions. These results show that reliable, untethered operations at depth are feasible, highlighting the potential of resident ROV systems for scalable, cost-effective underwater monitoring.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
