Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments
Juan David Hernández,
Klemen Istenič,
Nuno Gracias,
Narcís Palomeras,
Ricard Campos,
Eduard Vidal,
Rafael García,
Marc Carreras
Affiliations
Juan David Hernández
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Klemen Istenič
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Nuno Gracias
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Narcís Palomeras
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Ricard Campos
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Eduard Vidal
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Rafael García
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
Marc Carreras
Underwater Vision and Robotics Research Center (CIRS), Computer Vision and Robotics Institute (VICOROB), University of Girona, C\Pic de Peguera, 13 (La Creueta), 17003 Girona, Spain
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.
