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This paper presents the development of unmanned marine robotic control modelling and control synthesis using a coupled multivariable underactuated nonlinear adaptive U-model approach. The proposed controller was developed using thru an open source robot operating system (ROS) platform. The new adaptive coupled U-model based internal model control (IMC) node was successfully developed and tested. The proposed controller demonstrated the simplicity of the control synthesis process and the implementation of the mathematical algorithm in real-time. The controller was compared with the proven existing GIRONA 500 UUV for real-time performance. The ROS environment provides fast and reliable controller design and development compared to conventional software architecture. Simulation and real-time experiment were conducted using ROS via the GIRONA 500 UUV platform and compared with a PID mission controller. A new ROS node of nonlinear adaptive U-model based IMC was developed using ROS. The results showed good control signal convergence and tracking performance between the plant or system model with the proposed method This research was supported by the Yayasan Universiti Teknologi Petronas-Fundamental Research Grant-Petroleum Resource Fund (YUTP-FRG) funded by PRF under the grant 0015LC0-235, Universiti Teknologi PETRONAS, Malaysia and King Abdulaziz University, Jeddah, Saudi Arabia under the grant 015ME0-066

This thesis addresses the development of resources for accurate scaling and uncertainty estimation of image-based 3D models for scientific purposes based on data acquired with monocular or unsynchronized camera systems in difficult-to-access GPS-denied (underwater) environments. The developed 3D reconstruction framework allows the creation of textured 3D models based on optical and navigation data and is independent of a specific platform, camera or mission. The dissertation presents two new methods for automatically scaling of SfM-based 3D models using laser scalers. Both were used to perform an in-depth scale error analysis of large-scale models of deep-sea underwater environments to determine the advantages and limitations of image-based 3D reconstruction strategies. In addition, a novel SfM-based system is proposed to demonstrate the feasibility of producing a globally consistent reconstruction with its uncertainty while the robot is still in the water or shortly after Aquesta tesi aborda el desenvolupament de mètodes per a l'estimació precisa de l’escala i la incertesa de models 3D basats en imatges adquirides amb sistemes de càmeres monoculars o no sincronitzades en entorns submarins, de difícil accés i sense GPS. El sistema desenvolupat permet la creació de models 3D amb textura fent servir dades òptiques i de navegació, i és independent d’una plataforma, càmera o missió específica. La tesi presenta dos nous mètodes per a l’escalat automàtic de models 3D basats en SfM mitjançant mesuradors làser. Tots dos es van utilitzar per realitzar una anàlisi exhaustiva d'errors d’escalat de models en aigües submarines profundes per determinar avantatges i limitacions de les estratègies de reconstrucció 3D. A més, es proposa un nou sistema basat en SfM per demostrar la viabilitat de la reconstrucció 3D, globalment consistent, i amb informació d'incertesa mentre el robot encara està a l’aigua o poc després Esta tesis aborda el desarrollo de recursos para el escalado preciso y la estimación de la incertidumbre de modelos 3D basados en imágenes, y con fines científicos. El marco de reconstrucción 3D desarrollado permite la creación de modelos 3D texturizados basados en datos ópticos y de navegación, adquiridos con sistemas monoculares o no sincronizados de cámaras en entornos (submarinos) de difícil acceso sin disponibilidad de GPS. Además, presenta dos nuevos métodos para el escalado automático de modelos 3D basados en SfM mediante medidores laser. Ambos se utilizaron para analizar los errores en escala, de modelos de ambientes submarinos en aguas profundas, con el fin de determinar las ventajas y las limitaciones de las estrategias de reconstrucción 3D. Además, se propone un nuevo sistema para demostrar la viabilidad de una reconstrucción global consistente junto con su incertidumbre mientras el robot aún está en el agua o poco después Programa de Doctorat en Tecnologia

Following 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 sonar as a primary perception sensor to enable the vehicle operation in limited visibility conditions and overcome the possible turbidity arising during marine growth removal. Despite its advantages, working with acoustic data raises additional challenges for the processing and control methodologies involved. We present two chain link detectors that make use of forward-looking sonar and multibeam data and we combine them with adequate planning and control strategies to achieve a robust framework to detect, follow and map an underwater chain. Experiments conducted in a water tank and in a real harbor environment demonstrate the capability of autonomously detecting and following a chain with sufficient accuracy to perform subsequent cleaning or inspection tasks. Besides this, we demonstrate the possibility of obtaining a preliminary map of the chain and its surroundings regardless of visibility conditions This work was supported by the EU funded project PANDORA: Persistent Autonomy through learNing, aDaptation, Observation and ReplAnning”, ref. FP7-288273

Exploration of a complex underwater environment without an a priori map is beyond the state of the art for autonomous underwater vehicles (AUVs). Despite several efforts regarding simultaneous localization and mapping (SLAM) and view planning, there is no exploration framework, tailored to underwater vehicles, that faces exploration combining mapping, active localization, and view planning in a unified way. We propose an exploration framework, based on an active SLAM strategy, that combines three main elements: a view planner, an iterative closest point algorithm (ICP)-based pose-graph SLAM algorithm, and an action selection mechanism that makes use of the joint map and state entropy reduction. To demonstrate the benefits of the active SLAM strategy, several tests were conducted with the Girona 500 AUV, both in simulation and in the real world. The article shows how the proposed framework makes it possible to plan exploratory trajectories that keep the vehicle's uncertainty bounded; thus, creating more consistent maps., This research was funded by the Spanish State Research Agency through grants DPI2015-73978-JIN and DPI2017-89564-P, and the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656).

EU Marine Robots project grant agreement no. 731103 The marine robotics community is lacking a high quality simulator for doing scientific research, especially when it comes to testing control and vision algorithms in realistic underwater intervention tasks. All of the solutions used today are either outdated or try to combine different software tools, which often results in bad performance, stability issues and lack of important features. This paper presents a new software tool, focused on, but not limited to, simulation of intervention autonomous underwater vehicles (I-AUV). It delivers advanced hydrodynamics based on actual geometry, simulation of underwater sensors and actuators, as well as realistic rendering of underwater environment and ocean surface. It consists of a library written in C++ and a Robot Operating System (ROS) package Patryk Ciésslak has received funding from the European Community H2020 Programme under the Marie Skłodowska-Curie grant agreement no. 750063 and under EU Marine Robots project grant agreement no. 731103

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.

Marie Sklodowska-Curie grant agreement no. 750063 This paper presents a control architecture for an underwater vehicle-manipulator system (UVMS) to enable simultaneous tracking of end-effector configuration and contact force during floating-base manipulation. The main feature of the architecture is its combination of a task-priority (TP) kinematic control algorithm with a custom force control strategy, based on impedance (admittance) control. The TP algorithm used in the work includes recent treatment of equality and inequality tasks as well as original concepts to handle operation in singular configurations of the system. In the force control part the impedance concept is extended to allow for direct control over the value of exerted force and torque. Additional feed-forward signal is used to ensure stable contact. The performance of the control architecture is demonstrated by experiments in a test tank, with GIRONA500 I-AUV performing pipe inspection This work is part of a project titled ”Force/position control system to enable compliant manipulation from a floating IAUV”, which received funding from the European Union’s Horizon 2020 research and innovation programme, under the Marie Sklodowska-Curie grant agreement no. 750063

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 This work was partially funded through MINECO (grant number CTM2013-46718-R), the European Commission's Seventh Framework Programme as part of the project Morph (grant number FP7-ICT-2011-7-288704) and project Eurofleets2 (grant number FP7-INF-2012-312762), and the European Research Council (ERC Starting Grant "Robust Geometry Processing"; grant number 257474)

The use of commercially available autonomous underwater vehicles (AUVs) has increased during the last fifteen years. While they are mainly used for routine survey missions, there is a set of applications that nowadays can be only addressed by manned submersibles or work-class remotely operated vehicles (ROVs) equipped with teleoperated arms: the intervention applications. To allow these heavy vehicles controlled by human operators to perform intervention tasks, underwater structures like observatory facilities, subsea panels or oil-well Christmas trees have been adapted, making them more robust and easier to operate. The TRITON Spanish founded project proposes the use of a light-weight intervention AUV (I-AUV) to carry out intervention applications simplifying the adaptation of these underwater structures and drastically reducing the operational cost. To prove this concept, the Girona 500 I-AUV is used to autonomously dock into an adapted subsea panel and once docked perform an intervention composed of turning a valve and plugging in/unplugging a connector. The techniques used for the autonomous docking and manipulation as well as the design of an adapted subsea panel with a funnel-based docking system are presented in this article together with the results achieved in a water tank and at sea This work was supported by the Spanish project DPI2014-57746-C3 (MERBOTS Project) and by Generalitat Valenciana under Grant GVA-PROMETEO/2016/066. The University of Girona wants to thank the SARTI group for their collaboration with the TRITON project

International audience; Properly assessing the extent and magnitude of fault ruptures associated with large earthquakes is critical for understanding fault behavior and associated hazard. Submarine faults can trigger tsunamis, whose characteristics are defined by the geometry of seafloor displacement, studied primarily through indirect observations (e.g., seismic event parameters, seismic profiles, shipboard bathymetry, coring) rather than direct ones. Using deep-sea vehicles, we identify for the first time a marker of coseismic slip on a submarine fault plane along the Roseau Fault (Lesser Antilles), and measure its vertical displacement of ∼0.9 m in situ. We also map recent fissuring and faulting of sediments on the hangingwall, along ∼3 km of rupture in close proximity to the fault's base, and document the reactivation of erosion and sedimentation within and downslope of the scarp. These deformation structures were caused by the 2004 M w 6.3 Les Saintes earthquake, which triggered a subsequent tsunami. Their characterization informs estimates of earthquake recurrence on this fault and provides new constraints on the geometry of fault rupture, which is both shorter and displays locally larger coseismic displacements than available model predictions that lack field constraints. This methodology of detailed field observations coupled with near-bottom geophysical surveying can be readily applied to numerous submarine fault systems, and should prove useful in evaluating seismic and tsunamigenic hazard in all geodynamic contexts.

We present a novel method for planning coverage paths for inspecting complex structures on the ocean floor using an autonomous underwater vehicle (AUV). Our method initially uses a 2.5-dimensional (2.5D) prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions, while in regions with substantial 3D relief it follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle's state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. Toward that end, we present a replanning algorithm based on a 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 real time during the inspection mission, adapting the path according to the measurements provided by the vehicle's range-sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques we apply to the data acquired by the AUV to obtain 3D models of the inspected structures that show the benefits of our planning method for 3D mapping. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV, where we cover part of a breakwater structure in a harbor and an underwater boulder rising from 40 m up to 27 m depth This research has been sponsored by the Government of Spain (COMAROB Project, DPI2011-27977-C03-02), the MORPH EU FP7-Project (grant agreement FP7-ICT-2011-7-288704), and the Eurofleets2 EU FP7-Project (grant agreement FP7-INF-2012-312762). The authors are grateful to Lluis Magi, Carles Candela, and Arnau Carrera for helping with the GIRONA 500 operations

Underwater chain cleaning and inspection tasks are costly and time consuming operations that must be performed periodically to guarantee the safety of the moorings. We propose a framework towards an efficient and costeffective solution by using an autonomous underwater vehicle equipped with a forward-looking sonar. As a first step, we tackle the problem of individual chain link detection from the challenging forward-looking sonar data. To cope with occlusions and intensity variations due to viewpoint changes, the recognition problem is addressed as local pattern matching of the different link parts. We exploit the high frame-rate of the sonar to improve, by registration, the signal-to-noise ratio of the individual sonar frames and to cluster the local detections over time to increase robustness. Experiments with sonar images of a real chain are reported, showing a high percentage of correct link detections with good accuracy while potentially keeping real-time capabilities This work has been supported by the FP7-ICT-2011-7 project PANDORA-Persistent Autonomy through Learning, Adaptation, Observation and Re-planning (Ref 288273) funded by the European Commission and the Spanish Project ANDREA/RAIMON (Ref CTM2011-29691-C02-02) funded by the Ministry of Science and Innovation

This paper outlines the specifications and basic design approach taken on the development of the Girona 500, an autonomous underwater vehicle whose most remarkable characteristic is its capacity to reconfigure for different tasks. The capabilities of this new vehicle range from different forms of seafloor survey to inspection and intervention tasks Manuscript received April 1, 2011; revised August 5, 2011; accepted October 7, 2011. Date of publication November 30, 2011; date of current version January 9, 2012. Recommended by Guest Editor W. Kirkwood. This work was supported in part by the TRIDENT EU FP7-Project under Grant ICT-248497, in part by the Marie Curie PERG-GA-2010-276778 (Surf3DSLAM), and in part by the Spanish Government under the projects DPI2008-06548-C03 and CTM2010-15216/MAR

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments.

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position.

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories in cooperative ones. As a second feature, behavior state/action mapping is learnt by means of reinforcement learning (RL). A continuous Q-learning algorithm, implemented with a feed-forward neural network, is used. The behavior-based scheme attempts to fulfill simple missions in which several behaviors/tasks compete for the vehicle's control. The paper shows its feasibility with a target following mission designed to be carried out in a pool with the AUV ODIN. In the paper, simulation results are shown demonstrating the good performance of the hybrid method on behavior coordination as well as the convergence of the RL-based behaviors.

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors.

This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment.

This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed.

We propose an algorithm that extracts image features that are consistent with the 3D structure of the scene. The features can be robustly tracked over multiple views and serve as vertices of planar patches that suitably represent scene surfaces, while reducing the redundancy in the description of 3D shapes. In other words, the extracted features will off er good tracking properties while providing the basis for 3D reconstruction with minimum model complexity

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot.

El creixement de la robòtica (especialment en l'àrea dels sistemes intel·ligents) continua a grans passos, malgrat que encara no hi ha sistemes totalment autònoms per treballar en entorns complexos i desconeguts. Consideracions de cost, seguretat, temps de desenvolupament i altres, fan molt atractiva la teleoperació per a algunes tasques. És ben sabut que la interacció entre els operadors humans i els ordinadors encara és molt problemàtica (com es pot veure en les operacions de rescat del Titànic, Txernòbil i, més recentment, en la pèrdua d'un avió teleoperat a l'Afganistan). Aquests exemples fan ressaltar les dificultats inherents en la utilització de la informació i la teleoperació de robots. Una interfície persona-màquina (HMI) adequada podria resoldre aquest problemes, cosa que incrementaria la satisfacció de l'usuari i la utilització del sistema. Aquest projecte ofereix una contribució al desenvolupament i els criteris de disseny ergonòmic d'interfícies d'usuari per a sistemes teleoperats, especialment en el cas d'aplicacions amb robots submarins. Aquesta recerca es va desenvolupar com part del projecte GARBÍ, el robot submari teleoperat dissenyat per el Dr. Josep Amat i el seu equip, per ajudar als usuaris en les seves tasques marines. Una de les eines que ajuda a treballar millor un sistema teleoperat és la interfície persona-màquina (HMI) que serveix com canal de comunicació entre el sistema i l'usuari. Per iniciar el disseny de la interfície s'ha fet una recerca per determinar el marc teòric i l'estat de l'art en sistemes teleoperats, interfícies d'usuari i eines ergonomiques de disseny. S'han desenvolupat eines per mesurar qualitativament la qualitat de les interfícies persona-màquina (HMI) dels sistemes teleoperats presents en la literatura cientifica i determinar les millores que s'haurien d'introduir en les interficies en ordre de millorar la velocitat de transferencia d'informació.Les tasques de teleoperació han de mostrar una gran quantitat d'informació; aquesta situació es va resoldre en part mitjançant la realitat virtual, que es va fer servir com una eina per millorar les imatges de les càmeres. La realitat virtual, doncs, ajuda a resoldre alguns d'aquest problemes, com ara la representació espacial i la programació d'objectes. Aquest enfocament també permet una millora visual: la imatge real podria estar afectada per les condicions climàtiques (pluja, boirassa, etc.), per la part del dia (tarda, nit, etc.) i per l'entorn natural (la composició de l'aigua pot reduir la visibilitat submarina); la realitat virtual elimina tots aquests inconvenients i ofereix una imatge neta i filtrada. Un entorn virtual es va crear per introduir a l'usuari dintre de les tasques marines i totes les eines necessaries per la conducció del vehicle es van possar en la interfície. Per desenvolupar una interfície ergonómica i òptima s'ha d'involucrar als usuaris en el proces i aquestes activitats s'han de desenvolupar en forma especifica i organitzada. Durant aquesta recerca es van desenvolupar diverses interfícies persona-màquina, tenint en compte les necessitats i reaccions d'usuaris nous i experts. Dues interfícies es van desenvolupar per analitzar l'impacte de la visualització de la informació i la controlabilitat: una de les interfícies es va dissenyar amb finestres d'informació millorada per enfocar-la més a la visualització de dades i en l'altra es va simplificar el control i la manipulació del robot. El proces d'avaluació de les interfícies es va descriure, incloent una nova metodologia basat en els paràmetres d'utilització, la qual abasta diversos paràmetres i etapes de la interacció usuari-ordinador: la tasca, l'usuari i la interfície. Aquesta metodologia es va provar amb les interfícies desenvolupades i amb interfícies de jocs semblants., The growth of robotics -specially in intelligent systems- continues at an ever-faster pace, even though we still lack of totally autonomous systems to work in complex, unknown environments. Cost, safety needs and development time, among other considerations, make teleoperation an appealing way to perform some tasks. As we know, however, interaction between human operators and computers remains problematic -as can be seen in rescue operations from the Titanic to Chernobyl and, more recently, the missing teleoperated airplane in Afghanistan. These examples underscore the difficulties inherent in information utilization and robot teleoperation. An adequate user interface would solve these problems, increasing both user satisfaction and system usage. The present project offers a contribution to the development and ergonomic design rules of user interfaces for teleoperated systems, specifically in the case of underwater robot applications.Teleoperated robots are currently employed in different fields, for example: mine exploration, spatial and underwater research, high-risk exploration areas and other applications where human intelligence is indispensable. Kress (from IEEE Robotics & Automation Society) and others have pointed out that human machine interfaces (HMI) are critical to the success of teleoperation systems. A teleoperation task must display a great deal of information. Thus, virtual reality was added as a tool to enhance the plane camera images. Virtual reality helps solve some of those problems, e.g. spatial representation and object programming. This approach allows even for visual enhancement: the real image might be affected by weather conditions (rain, fog, etc.), time of the day (afternoon, night, etc.) and by natural environment (water composition can reduce underwater visibility). Virtual reality, allowing a clean, filtered image, would eliminate these and other inconveniences.As this research progressed, several human-machine interfaces (HMI) were developed, taking into account the needs and reactions of average as well as expert users. The interfaces were created with virtual reality tools and programmed in C language. Two interfaces were developed to analyze the impact of information visualization and controllability. One of them was designed with enhanced information windows to focus primarily on data visualization; while the other simplifies robot maneuverability and control. The fruit of this research allows for both a framework and guidelines for HMI design and a model for teleoperated human-machine interaction.In addition to the framework design, two interface evaluation methodologies were proposed. One, the Interface Index, is for rapid assessment. The other, the Usability Assessment, is for deep interface analysis, covering several parameters and stages in human-computer interaction. Several papers related to the development, design and evaluation of these interfaces have been published in international congresses related to this field.

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system.

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system.

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory.

This paper presents a new tracking system for autonomous underwater vehicles (AUVs) navigating in a close formation, based on computer vision and the use of active light markers. While acoustic localization can be very effective from medium to long distances, it is not so advantageous in short distances when the safety of the vehicles requires higher accuracy and update rates. The proposed system allows the estimation of the pose of a target vehicle at short ranges, with high accuracy and execution speed. To extend the field of view, an omnidirectional camera is used. This camera provides a full coverage of the lower hemisphere and enables the concurrent tracking of multiple vehicles in different positions. The system was evaluated in real sea conditions by tracking vehicles in mapping missions, where it demonstrated robust operation during extended periods of time This research was sponsored by the MORPH EU FP7-Project under Grant Agreement FP7-ICT-2011-7-288704, the Spanish National Project OMNIUS (Lightweight robot for omnidirectional underwater surveying and telepresence) under Agreement CTM2013-46718-R, the ROBOCADEMY (European Academy for Marine and Underwater Robotics) EU FP7-Project under Grant Agreement 608096, the Generalitat de Catalunya through the ACCIO (Agència per a la competitivitat de l’empresa de la Generalitat de Catalunya)/TecnioSpring program (TECSPR14-1-0050), with the support of “la Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya”