Coverage path planning with realtime replanning for inspection of 3d underwater structures

We present a novel method for planning coverage paths for inspecting complex structures on the ocean floor using an autonomous underwater vehicle (AUV). Our method initially uses a 2.5D prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions while, in regions with substantial 3D relief, follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle’s state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. To this aim, we present a replanning algorithm based on stochastic trajectory optimization that reshapes the nominal path to cope with the actual target structure perceived in situ. The replan-ning algorithm runs onboard the AUV in realtime during the inspection mission, adapting the path according to the measurements provided by the vehicle’s range sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques w