Kasno Mohammad Afif, Yahaya Izzat Nadzmi, Jung Jin-Woo
Department of Computer Science and Engineering, Dongguk University, Seoul 04620, Republic of Korea.
Faculty of Electronic Technology and Engineering, Universiti Teknikal Malaysia Melaka, Malacca 76100, Malaysia.
Sensors (Basel). 2024 Aug 6;24(16):5097. doi: 10.3390/s24165097.
ROV operators often encounter challenges with orientation awareness while operating underwater, primarily due to relying solely on 2D camera feeds to manually control the ROV robot arm. This limitation in underwater visibility and orientation awareness, as observed among Malaysian ROV operators, can compromise the accuracy of arm placement, and pose a risk of tool damage if not handle with care. To address this, a 3D orientation monitoring system for ROVs has been developed, leveraging measurement sensors with nine degrees of freedom (DOF). These sensors capture crucial parameters such as roll, pitch, yaw, and heading, providing real-time data on the ROV's position along the X, Y, and Z axes to ensure precise orientation. These data are then utilized to generate and process 3D imaging and develop a corresponding 3D model of the operational ROV underwater, accurately reflecting its orientation in a visual representation by using an open-source platform. Due to constraints set by an agreement with the working class ROV operators, only short-term tests (up to 1 min) could be performed at the dockyard. A video demonstration of a working class ROV replica moving and reflecting in a 3D simulation in real-time was also presented. Despite these limitations, our findings demonstrate the feasibility and potential of a cost-effective 3D orientation visualization system for working class ROVs. With mean absolute error (MAE) error less than 2%, the results align with the performance expectations of the actual working ROV.
遥控水下机器人（ROV）操作员在水下操作时经常遇到方向感知方面的挑战，主要原因是仅依靠二维摄像头画面来手动控制ROV的机械臂。正如马来西亚ROV操作员所观察到的，水下能见度和方向感知的这种局限性可能会影响机械臂放置的准确性，如果不小心操作，还可能造成工具损坏。为了解决这个问题，已经开发了一种用于ROV的三维方向监测系统，该系统利用了具有九个自由度（DOF）的测量传感器。这些传感器捕捉诸如横滚、俯仰、偏航和航向等关键参数，提供关于ROV在X、Y和Z轴上位置的实时数据，以确保精确的方向。然后利用这些数据生成和处理三维成像，并开发相应的水下作业ROV的三维模型，通过使用开源平台在视觉呈现中准确反映其方向。由于与工人阶级ROV操作员达成的协议所设定的限制，只能在造船厂进行短期测试（最长1分钟）。还展示了一个工人阶级ROV复制品在三维模拟中实时移动和反射的视频演示。尽管有这些限制，我们的研究结果证明了一种具有成本效益的工人阶级ROV三维方向可视化系统的可行性和潜力。平均绝对误差（MAE）小于2%，结果符合实际作业ROV的性能预期。
