Oceanalpha L25 USV Conduct Underwater Topographic Mapping

In this video Oceanalpha demonstrates how its L25 USV obtained the point cloud data of the underwater terrains, to provide data support for the diagnosis of structure sedimentation and deformation and back siltation to the Hong Kong- Zhuhai – Macao bridge.

The Hong Kong-Zhuhai-Macao Bridge is the longest sea-crossing bridge in the world. Its sea section is 42 kilometers, and the undersea tunnel is 35.578 kilometers long. The long-term inspection and maintenance of the bridge are difficult and dangerous if rely purely on manual operation. Adopting autonomous unmanned technology can greatly improve efficiency and ensure personnel safety.

Mapping Process

According to client’s requirement, the underwater terrain mapping task was carried out in a water area of 500 meters × 200 meters above the immersed tube tunnel at the Zhuhai end of the bridge, and another task was performed in the water area within 100 meters of the West Artificial Island. The OceanAlpha L25 marine USV was equipped with a Teledyne RESON T50-P multibeam sounder for line-tracking mapping.

The L25 USV arrived at the operation area after 20 kilometers of autonomous navigation. Technicians laid the waypoint lines in accordance with “GBT 12763.10-2007 Marine Survey Specification: Submarine Topography and Landform Survey” and “GB 12327-1998 Hydrographic Survey Specification”.

The main waypoint lines were set according to the overall direction of the target area. The overlap of adjacent sweeps is not less than 10% of the sweep width, and the contact waypoint line is not shorter than 5% of the total length of the mainline. By scanning the two underwater areas, L25 USV obtained the point cloud data of the underwater terrains, which provides data support for the diagnosis of structure sedimentation and deformation and back siltation.

Conclusion

The application of unmanned technology can effectively improve operational efficiency and reduce personnel safety risks. Users can save periodic monitoring tasks in the system so that the USV can intelligently control its navigation based on high-precision position and speed information, thereby performing highly repetitive monitoring tasks. In this mode, the periodic historical data formed by using the same set of equipment and the same mapping path is more reliable, continuous, easy to compare and traceable than traditional manned operations.