Autonomous underwater navigation and optical mapping in unknown natural environments

Abstract

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario

This work was supported by MORPH, Excellabust, and Roboacademy European projects (FP7-ICT-2011-7-288704, H2020-TWINN-2015 (CSA)-691980, and FP7-PEOPLE-2013-ITN-608096), the ARCHROV Spanish project (DPI2014-57746-C3-3-R), the Generalitat de Catalunya through the ACCIO/TecnioSpring program (TECSPR14-1-0050), and partially supported by the Colombian Government through its Predoctoral Grant Program (No. 568) offered by Colciencias