Natàlia Hurtós

Fourier-based Registration for Robust Forward-looking Sonar Mosaicing in Low-visibility Underwater Environments

Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping.

Toward persistent autonomous intervention in a subsea panel

Intervention autonomous underwater vehicles (I-AUVs) have the potential to open new avenues for the maintenance and monitoring of offshore subsea facilities in a cost-effective way. However, this requires challenging intervention operations to be carried out persistently, thus minimizing human supervision and ensuring a reliable vehicle behaviour under unexpected perturbances and failures. This paper describes a system to perform autonomous intervention—in particular valve-turning—using the concept of persistent autonomy. To achieve this goal, we build a framework that integrates different disciplines, involving mechatronics, localization, control, machine learning and planning techniques, bearing in mind robustness in the implementation of all of them. We present experiments in a water tank, conducted with Girona 500 I-AUV in the context of a multiple intervention mission. Results show how the vehicle sets several valve panel configurations throughout the experiment while handling different errors, either spontaneous or induced. Finally, we report the insights gained from our experience and we discuss the main aspects that must be matured and refined in order to promote the future development of intervention autonomous vehicles that can operate, persistently, in subsea facilities.

Real-time mosaicing with two-dimensional forward-looking sonar

Forward-looking sonar can be used for underwater mapping when water visibility is poor. The generation of an acoustic mosaic of the environment is of high interest when underwater vehicles are used for surveys or search tasks. Moreover, if the mosaic is generated in real-time it can be used to provide instantaneous location feedback (e.g. to a ROV pilot or to an AUV), to ensure complete coverage of an area or facilitate the immediate location of targets. In this paper, we present an approach for achieving such a real-time mosaicing capability. Our system considers a simplified imaging model and estimates 2D sonar motions from the pairwise registration of sonar frames. The registration is performed by using a Fourier-based technique, avoiding the extraction of features and ensuring a fast implementation. The mosaicing problem is formulated using a pose graph, with the vertices being the sonar image positions and the edges being constraints from the vehicle odometry and the registration of consecutive and non-consecutive frames. The graph is incrementally optimized using the g2o framework and the optimized poses are then used to build the mosaic online. We apply the method on data gathered on real conditions and show that the resulting sonar mosaic closely matches both the offline generated mosaic as well as ground truth measurements while operating under real-time constraints.

Calibration of optical camera coupled to acoustic multibeam for underwater 3D scene reconstruction

Combination of optical and acoustic sensors to compensate the strengths and weaknesses of each sensor modality is a topic of increasing interest in applications involving autonomous underwater vehicles (AUV). In this work, an opti-acoustic system composed by a single camera and a multibeam sonar is proposed, providing a simulation environment to validate its potential use in 3D reconstruction. Since extrinsic calibration is a prerequisite for this kind of feature-level sensor fusion, an effective approach to address the calibration problem between a multibeam and a camera is presented.

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.

Sonar-based chain following using an autonomous underwater vehicle

Tracking an underwater chain using an autonomous vehicle can be a first step towards more efficient solutions for cleaning and inspecting mooring chains. We propose to use a forward looking sonar as a primary perception sensor to enable the vehicle operation in limited visibility conditions and overcome the turbidity arisen during marine growth removal. Despite its advantages, working with acoustic imagery raises additional challenges to the involved image processing and control methodologies. In this paper we present a robust framework to perform chain following, combining perception, planning and control disciplines. We first introduce a detection system that exploits the sonars high frame rate and applies local pattern matching to handle the complexity of detecting link chains in acoustic images. Then, a planning system deals with the dispersed detections and determines the link waypoints that the vehicle should reach. Finally, the vehicle is guided through these waypoints using a high level controller that has been tailored to simultaneously traverse the chain and keep track of upcoming links. Experiments on real data demonstrate the capability of autonomously follow a chain with sufficient accuracy to perform subsequent cleaning or inspection tasks.

Team-Based Building of a Remotely Operated Underwater Robot, an Innovative Method of Teaching Engineering

This article reports the experience gathered along 6 years in developing a team-based project activity to promote engineering programs among secondary school students. The aim of the activity is to increase the interest of students for science and technology in general, but also to promote engineering skills, capabilities and values, leading to attract more secondary school students to enrolment for engineering programs. Simple theoretical concepts related to physics and engineering are illustrated through hands-on experimentation. To achieve this goal, the students build a remotely operated underwater robot in a workshop. The robot is built using low-cost materials and the students customize their own design over the different phases of the workshop. Once the activity is completed, every team understands that with teamwork, effort and a good working strategy, every problem can be overcome.

Cognitive system for autonomous underwater intervention

Learning by demonstration (LbD) has been adapted to the underwater domain.LbD has been extended to control simultaneously an AUV and its manipulator.An underwater valve turning task has been used to test the LbD algorithm.The autonomously reproduced task achieves similar performance as human operator.The method proves to be resilient to perturbations. The implementation of autonomous intervention tasks with underwater vehicles is a non-trivial issue due to the challenging and dynamic conditions of the underwater medium (e.g., water current perturbations, water visibility). Likewise, it requires a significant programming effort each time that the vehicle must perform a different manipulation operation. In this paper we propose, instead, to use a cognitive system that learns the intervention task from an expert operator through an intuitive learning by demonstration (LbD) algorithm. Taking as an input few operator demonstrations, the algorithm generalizes the task knowledge into a model and is able to control the vehicle and the manipulator simultaneously to reproduce the task, thus conferring a more adaptive behavior in front of the environment changes and allowing to easily transfer the knowledge of new tasks. A cognitive architecture has been implemented in order to integrate the LbD algorithm with the onboard sensors and actuators and to allow its interplay with the vehicle perception, control and navigation modules. To validate the full framework we present real experiments in a water tank using an AUV equipped with a four DoF manipulator. A human operator teaches the system to perform a valve turning intervention and we analyze the results of multiple task reproductions, including cases under the effect of water current perturbations, showing the success of the system in autonomously reproducing the task.

Rotation Estimation for Two-Dimensional Forward-Looking Sonar Mosaicing

Two-dimensional forward-looking sonars are becoming standard sensors in both remotely operated and autonomous underwater vehicles, increasing the possibility of mapping under low visibility conditions. Due to the inherent nature of sonar image formation, the ideal mapping strategy relies on maintaining the same orientation, so as to minimize intensity alterations due to viewpoint changes. However, this is not always possible and therefore it is necessary to deal with the registration of sonar images under rotational movements. Previous investigations have discouraged the use of feature-based techniques and have suggested the use of global methods that are robust to noise, low-resolution and inhomogeneous insonification and can deal with the decoupled estimation of roto-translations. In this paper we review several candidate methods and assess them by using real data gathered under different conditions. By identifying the best approach for rotation estimation we aim to extend the applicability of sonar mosaicing to more diverse scenarios. Results indicate that applying phase correlation directly to polar frames leads to the highest accuracy under most cases.

LOON-DOCK: AUV homing and docking for high-bandwidth data transmission

Persistent deployment of underwater assets holds the key to achieve consistent, long-term undersea monitoring. To advance in that direction, the LOON-DOCK project aims to demonstrate remote AUV operation and survey data transmission through the Internet using an underwater docking station. We present a funnel-shaped docking station equipped with a contactless high bandwidth link and the necessary equipment to enable autonomous homing and docking by combining acoustic and optical sensing. The proposed combination, using a range-only localization at far distances and a light beacon localization at short ranges ensures a reliable strategy enabled with low-cost equipment and minimal requirements on both the vehicle and the dock sides. Moreover, remote operation is demonstrated by integrating the system in a unified web interface to control underwater assets, thus allowing a user to operate the AUV remotely through Internet. The full system has been successfully validated with tests conducted in a harbor environment.