Ricard Campos

A surface reconstruction method for in-detail underwater 3D optical mapping

Underwater range scanning techniques are starting to gain interest in underwater exploration, providing new tools to represent the seafloor. These scans (often) acquired by underwater robots usually result in an unstructured point cloud, but given the common downward-looking or forward-looking configuration of these sensors with respect to the scene, the problem of recovering a piecewise linear approximation representing the scene is normally solved by approximating these 3D points using a heightmap (2.5D). Nevertheless, this representation is not able to correctly represent complex structures, especially those presenting arbitrary concavities normally exhibited in underwater objects. We present a method devoted to full 3D surface reconstruction that does not assume any specific sensor configuration. The method presented is robust to common defects in raw scanned data such as outliers and noise often present in extreme environments such as underwater, both for sonar and optical surveys. Moreover, the proposed method does not need a manual preprocessing step. It is also generic as it does not need any information other than the points themselves to work. This property leads to its wide application to any kind of range scanning technologies and we demonstrate its versatility by using it on synthetic data, controlled laser scans, and multibeam sonar surveys. Finally, and given the unbeatable level of detail that optical methods can provide, we analyze the application of this method on optical datasets related to biology, geology and archeology.

Tectonic structure, evolution, and the nature of oceanic core complexes and their detachment fault zones (13°20'N and 13°30'N, Mid-Atlantic Ridge)

Microbathymetry data, in situ observations, and sampling along the 138200N and 138200N oceanic core complexes (OCCs) reveal mechanisms of detachment fault denudation at the seafloor, links between tectonic extension and mass wasting, and expose the nature of corrugations, ubiquitous at OCCs. In the initial stages of detachment faulting and high-angle fault, scarps show extensive mass wasting that reduces their slope. Flexural rotation further lowers scarp slope, hinders mass wasting, resulting in morphologically complex chaotic terrain between the breakaway and the denuded corrugated surface. Extension and drag along the fault plane uplifts a wedge of hangingwall material (apron). The detachment surface emerges along a continuous moat that sheds rocks and covers it with unconsolidated rubble, while local slumping emplaces rubble ridges overlying corrugations. The detachment fault zone is a set of anostomosed slip planes, elongated in the alongextension direction. Slip planes bind fault rock bodies defining the corrugations observed in microbathymetry and sonar. Fault planes with extension-parallel stria are exposed along corrugation flanks, where the rubble cover is shed. Detachment fault rocks are primarily basalt fault breccia at 138200N OCC, and gabbro and peridotite at 138300N, demonstrating that brittle strain localization in shallow lithosphere form corrugations, regardless of lithologies in the detachment zone. Finally, faulting and volcanism dismember the 138300N OCC, with widespread present and past hydrothermal activity (Semenov fields), while the Irinovskoe hydrothermal field at the 138200N core complex suggests a magmatic source within the footwall. These results confirm the ubiquitous relationship between hydrothermal activity and oceanic detachment formation and evolution.

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

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 vehicles 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 vehicles 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.

The Kallisti Limnes, carbon dioxide-accumulating subsea pools

Natural CO2 releases from shallow marine hydrothermal vents are assumed to mix into the water column, and not accumulate into stratified seafloor pools. We present newly discovered shallow subsea pools located within the Santorini volcanic caldera of the Southern Aegean Sea, Greece, that accumulate CO2 emissions from geologic reservoirs. This type of hydrothermal seafloor pool, containing highly concentrated CO2, provides direct evidence of shallow benthic CO2 accumulations originating from sub-seafloor releases. Samples taken from within these acidic pools are devoid of calcifying organisms, and channel structures among the pools indicate gravity driven flow, suggesting that seafloor release of CO2 at this site may preferentially impact benthic ecosystems. These naturally occurring seafloor pools may provide a diagnostic indicator of incipient volcanic activity and can serve as an analog for studying CO2 leakage and benthic accumulations from subsea carbon capture and storage sites.

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments

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.

Splat-based surface reconstruction from defect-laden point sets

We introduce a method for surface reconstruction from point sets that is able to cope with noise and outliers. First, a splat-based representation is computed from the point set. A robust local 3D RANSAC-based procedure is used to filter the point set for outliers, then a local jet surface - a low-degree surface approximation - is fitted to the inliers. Second, we extract the reconstructed surface in the form of a surface triangle mesh through Delaunay refinement. The Delaunay refinement meshing approach requires computing intersections between line segment queries and the surface to be meshed. In the present case, intersection queries are solved from the set of splats through a 1D RANSAC procedure.

Underwater Multi-Vehicle Trajectory Alignment and Mapping Using Acoustic and Optical Constraints

Multi-robot formations are an important advance in recent robotic developments, as they allow a group of robots to merge their capacities and perform surveys in a more convenient way. With the aim of keeping the costs and acoustic communications to a minimum, cooperative navigation of multiple underwater vehicles is usually performed at the control level. In order to maintain the desired formation, individual robots just react to simple control directives extracted from range measurements or ultra-short baseline (USBL) systems. Thus, the robots are unaware of their global positioning, which presents a problem for the further processing of the collected data. The aim of this paper is two-fold. First, we present a global alignment method to correct the dead reckoning trajectories of multiple vehicles to resemble the paths followed during the mission using the acoustic messages passed between vehicles. Second, we focus on the optical mapping application of these types of formations and extend the optimization framework to allow for multi-vehicle geo-referenced optical 3D mapping using monocular cameras. The inclusion of optical constraints is not performed using the common bundle adjustment techniques, but in a form improving the computational efficiency of the resulting optimization problem and presenting a generic process to fuse optical reconstructions with navigation data. We show the performance of the proposed method on real datasets collected within the Morph EU-FP7 project.

Kornati bathymetry survey data-set for navigation and mapping

This paper reports a navigation and mapping data-set collected in the Croatian Kornati Archipielago during the “Breaking the Surface 2010” International Interdisciplinary Field Training of Marine Robotics and Applications event. A sensor ridge including a navigation and mapping sensor suite, to be later installed in the GIRONA500 AUV being developed a the university of Girona, was attached to a motor boat to collect geo-referenced data. The sensor suite includes a Multibeam sonar profiler, an AHRS, a DGPS, a sound-speed profiler including a depth cell, a video camera and a mechanical scanning sonar profiler. The paper reports the experiment performed as well as the navigation and mapping results using: 1) GPS only (used as a ground truth), 2) Dead Reckoning only, and 3) a preliminary method fusing dead reckoning with surface registration based on a simple modification of the well known ICP algorithm. Preliminary, but promising, results show that a better performance may be achieved using the last method.

Surface meshing of underwater maps from highly defective point sets

Owing to the many possible errors that may occur during real-world mapping, point set maps often present a huge amount of outliers and large levels of noise. We present two robust surface reconstruction techniques dealing with corrupted point sets without resorting to any prefiltering step. They are based on building an unsigned distance function, discretely evaluated on an adaptive tetrahedral grid, and defined from an outlier-robust splat representation. To extract the surface from this volumetric view, the space is partitioned into two subsets, the surface of interest being at the boundary separating them. While both methods are based on a similar graph definition derived from the above-mentioned grid, they differ in the partitioning procedure. First, we propose a method using S-T cuts to separate the inside and outside of the mapped area. Second, we use a normalized cut approach to partition the volume using only the values of the unsigned distance function. We prove the validity of our methods by applying them to challenging underwater data sets (sonar and image based), and we benchmark their results against the approaches in the state of the art.

Underwater caves sonar data set

This paper describes a data set collected with an autonomous underwater vehicle testbed in the unstructured environment of an underwater cave complex. The vehicle is equipped with two mechanically scanned imaging sonar sensors to simultaneously map the caves horizontal and vertical surfaces, a Doppler velocity log, two inertial measurement units, a depth sensor, and a vertically mounted camera imaging the sea floor for ground truth validation at specific points. The testbed collected the data in July 2013, guided by a human diver, to sidestep autonomous navigation in a complex environment. For ease of use, the original robot operating system bag files are provided together with a version combining imagery and human-readable text files for processing on other environments.