Planning coverage paths on bathymetric maps for in-detail inspection of the ocean floor

This paper proposes a coverage path planning (CPP) method for inspection of 3D natural structures on the ocean floor charted as 2.5D bathymetric maps. This task is integral to many marine robotics applications, such as microbathymetry mapping and image photo-mosaicing. We consider an autonomous underwater vehicle (AUV) with hovering capabilities imaging the ocean floor with an orientable sensor, such as a camera or a sonar. While standard lawnmower-type surveys at constant altitude are well-suited for covering effectively planar areas, two major problems arise when tracing such paths over high-relief terrain. First, the sudden depth changes required by such paths imply very costly motions, as moving in the vertical axis is expensive for most AUVs. Second, some time is required to adjust the vehicle depth after a sudden change in the relief, resulting in a varying distance from the target surface which deteriorates the overall quality of the collected imaging data. The method proposed in this paper accounts for these facts and generates different coverage patterns according to terrain's relief, resulting in a well-suited coverage path for imaging tasks. The proposed CPP method is fast and easy to implement, and provides a valuable tool for planning coverage paths in marine environments. We tested the proposed method on a real-world bathymetric dataset of a lava tongue obtained during recent sea trials in the Santorini caldera in Greece and compares favorably to a standard lawnmower-type survey path.