Towards Autonomous Industrial-Scale Bathymetric Surveying
This work addresses cost and efficiency challenges in industrial seabed surveying for tasks like pipeline installation, though it appears incremental as it builds on existing SLAM methods.
The paper tackles the problem of automating bathymetric surveying for offshore applications by presenting a SLAM system that optimizes geo-referencing through sensor fusion and geometric consistency maximization, demonstrating robustness across terrains and improved map consistency even in areas with low topographic variation.
Both higher efficiency and cost reduction can be gained from automating bathymetric surveying for offshore applications such as pipeline, telecommunication or power cables installation and inspection on the seabed. We present a SLAM system that optimizes the geo-referencing of bathymetry surveys by fusing the dead-reckoning sensor data from the surveying vehicle with constraints from the maximization of the geometric consistency of overlapping regions of the survey. The framework has been extensively tested on bathymetric maps from both simulation and several actual industrial surveys and has proved robustness over different types of terrain. We demonstrate that our system is able to maximize the consistency of the final map even when there are large sections of the survey with reduced topographic variation. The framework has been made publicly available together with the simulation environment used to test it and some of the datasets.