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.

翻译：我们对海洋的理解仍然受限于稀疏且不频繁的观测，这主要是因为当前方法受制于水下监测的高成本和后勤难度，要么依赖跨广阔区域的零星调查，要么依赖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、自主的运行。尽管近期有所进展，但在自治性、机器人鲁棒性及机械可靠性方面仍存在持续性挑战，尤其是在恶劣偏远环境下的长期部署，导致驻留式水下航行器仍不常见。本文通过展示一种在90米深度使用对接站与微型遥控潜水器（ROV）的驻留式基础设施的开发、部署与运行，来解决这些问题。该ROV配备了增强的机载处理与感知能力，使其能够利用超短基线（USBL）信号自主导航，通过基于ArUco标记并通过扩展卡尔曼滤波融合的视觉定位进行对接，并执行局部巡检任务。该系统实现了90%的自主对接成功率，并在四分钟内完成了完整的巡检任务，验证了声学与视觉导航在实际环境中的集成。这些结果表明，在深海进行可靠的无线运行是可行的，凸显了驻留式ROV系统在可扩展、成本效益高的水下监测方面的潜力。