Multisensor online 3D view planning for autonomous underwater exploration

Abstract

AbstractThis study presents a novel octree‐based three‐dimensional (3D) exploration and coverage method for autonomous underwater vehicles (AUVs). Robotic exploration can be defined as the task of obtaining a full map of an unknown environment with a robotic system, achieving full coverage of the area of interest with data from a particular sensor or set of sensors. While most robotic exploration algorithms consider only occupancy data, typically acquired by a range sensor, our approach also takes into account optical coverage, so the environment is discovered with occupancy and optical data of all discovered surfaces in a single exploration mission. In the context of underwater robotics, this capability is of particular interest, since it allows one to obtain better data while reducing operational costs and time. This study expands our previous study in 3D underwater exploration, which was demonstrated through simulation, presenting improvements in the view planning (VP) algorithm and field validation. Our proposal combines VP with frontier‐based (FB) methods, and remains light on computations even for 3D environments thanks to the use of the octree data structure. Finally, this study also presents extensive field evaluation and validation using the Girona 500 AUV. In this regard, the algorithm has been tested in different scenarios, such as a harbor structure, a breakwater structure, and an underwater boulder.