Online view planning for inspecting unexplored underwater structures

In this paper, we propose a method to automate the exploration of unknown underwater structures for autonomous underwater vehicles (AUVs). The proposed algorithm iteratively incorporates exteroceptive sensor data and replans the next-best-view (NBV) in order to fully map an underwater structure. This approach does not require prior environment information. However, a safe exploration depth and the exploration area (defined by a bounding box, parametrized by its size, location and resolution) must be provided by the user. The algorithm operates online by iteratively conducting the following three tasks: 1) Profiling sonar data is firstly incorporated into a 2-dimensional (2D) grid map, where voxels are labeled according to their state (a voxel can be labeled as empty, unseen, occluded, occplane, occupied or viewed). 2) Useful viewpoints to continue exploration are generated according to the map. 3) A safe path is generated to guide the robot towards the next viewpoint location. Two sensors are used in this approach: a scanning profiling sonar, which is used to build an occupancy map of the surroundings, and an optical camera, which acquires optical data of the scene. Finally, in order to demonstrate the feasibility of our approach we provide real-world results using the Sparus II AUV