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

摘要

We present a novel method for planning 3D coverage paths for inspection of complex structures on the ocean floor (such as seamounts or coral reefs) using an autonomous underwater vehicle (AUV). Our method initially uses an a priori map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target structure. We then go beyond previous approaches in the literature by considering the vehicle's position 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 replanning 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. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV where we cover a concrete block of a breakwater structure in a harbor and an underwater boulder rising from 40 m up to 27 m depth. Moreover, we apply state-of-the-art surface reconstruction techniques to the data acquired by the AUV and obtain 3D models of the inspected structures that show the benefits of our planning method for 3D mapping.