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 90m depth. The ROVis 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.

翻译：我们对海洋的认识仍受限于稀疏且不频繁的观测，这主要是因为现有方法受限于水下监测的高成本和高后勤投入，主要依赖于大范围的零星勘测或固定地点的长期测量。为克服这些限制，监测系统必须能够在无需持续水面支持的情况下实现持久自主作业。尽管近期取得了进展，但由于在自主性、机器人适应性和机械鲁棒性方面持续存在的挑战，尤其是在恶劣偏远环境下的长期部署，常驻水下航行器仍不常见。本研究通过介绍一个在90米水深使用对接站与迷你级遥控潜水器（ROV）构成的常驻基础设施的开发、部署与运行，以解决这些问题。该ROV配备了增强的机载处理与感知能力，使其能够利用USBL信号自主导航，通过基于ArUco标记的视觉定位（经扩展卡尔曼滤波融合）进行对接，并执行局部巡检任务。该系统实现了90%的自主对接成功率，并在四分钟内完成完整的巡检任务，验证了声学与视觉导航在真实环境中的集成。这些结果表明，在深水环境中实现可靠的无缆作业是可行的，凸显了常驻ROV系统在可扩展、高性价比水下监测方面的潜力。