Abstract
Monitoring offshore infrastructure is a challenging task owing to the harsh ocean environment. To reduce human involvement in this task, this study proposes an autonomous surface vehicle (ASV)-based structural monitoring system for inspecting power cable lines under the ocean surface. The proposed ASV was equipped with multimodal sonar sensors, including a multibeam echosounder (MBES) and side-scan sonar (SSS) for mapping the seafloor, combined with a precisely estimated vehicle pose from navigation sensors. In particular, a globally consistent map was developed using the orthometric height as a vertical datum estimated based on the geoid height received from the GPS. Accordingly, the MBES and SSS generate a map of the target objects in the form of point clouds and sonar images, respectively. Dedicated outlier removal methods for MBES sensing were proposed to preserve the sparse inlier point cloud, and we applied the projection of the SSS image pixels to reflect the geometry of the seafloor. A field test was conducted in an ocean environment using real offshore cable lines to verify the efficiency of the proposed monitoring system.
Highlights
Ocean System Engineering Research Division, Korea Research Institute of Ships and Ocean Engineering, Abstract: Monitoring offshore infrastructure is a challenging task owing to the harsh ocean environment
As the seafloor near Jeju Island is mainly composed of basalt, the sonar beams suffer from random reflections
The sonar image produced a patchy image owing to the high roll and pitch motion of the autonomous surface vehicle (ASV) caused by the ocean waves and the new pixels drawn on top of the old pixels
Summary
The base platform of the ASV was designed based on a catamaran to enable a differential thrust. The MBES and SSS were installed in the middle of the main hulls on the stern and bow sides, respectively. Three high-performance lithium batteries were installed for electrical power. A GPS receiver and an attitude heading reference system (AHRS) were installed to acquire the real-time motion information of the vehicle. Wireless local area networks using wireless fidelity and radio frequency devices were deployed to reciprocally communicate operating commands and the current state of the vehicle. ASV, including the payload sensors for navigation and mapping
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