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The presented article describes the design features of an educational robotics project addressed for secondary school students and carried out at the University of Girona (UdG). The project, called Underwater Robotics Workshop, is about the students building an underwater exploration robotic vehicle using low-cost materials. Its ultimate objective is to promote engineering interest among students and motivate them to direct their future studies towards engineering degrees. The main purpose of this article is to describe this activity and to promote it. Versatility and adaptation are key values as the activity has been designed to be adapted to convenience or replicated. It is a continuation work of a previously published articles, now describing different technological adaptations related to the design of the vehicle’s controller, and the gathered experiences from added workshop celebrations in the recent years. The workshop has been defined as a project-based learning approach where the students learn about physics, engineering, electronics, programming, and robotics, as well as to use all kinds of working tools, according to the maker philosophy. To date, the opinions collected from the participants encourage continuation of the activity and, at the same time, ask for the introduction of novelties to keep the workshop updated with the contents of the subjects related to technology and sciences. This project is being held for more than 13 years in the UdG. More than 800 secondary school students have participated in the activity, building about 200 underwater vehicles in more than 50 editions of the workshop This work has been partially funded by the Catalan Government (Generalitat de Catalunya) through ACDC grant number 2012ACDC00129, ACDC grant number 2011ACDC00023, ACDC grant number 2010ACDC00127 and ACDC grant number 2009ACDC00158

Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier.

In this study, an antagonistic actuator using dielectric elastomer actuators (DEAs) is developed to investigate the use of rolled DEAs in underwater robots. The actuator consists of a backbone, an elastic hinge, and two rolled DEAs placed in an antagonistic fashion, allowing for the generation of bidirectional movements of the actuator tip. To prove this concept, an analytical model of the actuator is built. The experimental samples are fabricated based on the specification determined by the model. In the fabricated actuator, each rolled DEA has a diameter of 6 mm and a length of 21 mm. The whole device weighs 1.7 g. In the tested voltage range of 0–1200 V, the actuator exhibits a voltage-controllable angle and torque of up to 2.2° and 11.3 mN∙mm, respectively. The actuator is then implemented into a swimming robot, which shows forward speed of 0.9 mm/s at the applied voltage of 1000 V and the driving frequency of 10 Hz. The results demonstrate the feasibility of using rolled DEAs in underwater robots.

Underwater robots are often used in marine exploration and development to assist divers in underwater tasks. However, the underwater robots on the market have some problems, such as only a single function of object detection or tracking, the use of traditional algorithms with low accuracy and robustness, and the lack of effective interaction with divers. To this end, we designed a type of gesture recognition based on interaction, using person tracking as an auxiliary means for an underwater accompanying robot (UAR). We train and test the SSDLite detection algorithm using the self-labeled underwater datasets, and combine the kernelized correlation filters (KCF) tracking algorithm with the “Active Control” target tracking rule to continuously track the underwater human body. Our experiments show that the use of underwater datasets and target tracking can effectively improve gesture recognition accuracy by 40–105%. In the outfield experiment, the performance of the algorithm was good. It achieved target tracking and gesture recognition at 29.4 FPS on Jetson Xavier NX, and the UAR made corresponding actions according to the diver gesture command.

Undulatory swimming represents an ideal behavior to investigate locomotion control and the role of the underlying central and peripheral components in the spinal cord. Many vertebrate swimmers have central pattern generators and local pressure-sensitive receptors that provide information about the surrounding fluid. However, it remains difficult to study experimentally how these sensors influence motor commands in these animals. Here, using a specifically designed robot that captures the essential components of the animal neuromechanical system and using simulations, we tested the hypothesis that sensed hydrodynamic pressure forces can entrain body actuation through local feedback loops. We found evidence that this peripheral mechanism leads to self-organized undulatory swimming by providing intersegmental coordination and body oscillations. Swimming can be redundantly induced by central mechanisms, and we show that, therefore, a combination of both central and peripheral mechanisms offers a higher robustness against neural disruptions than any of them alone, which potentially explains how some vertebrates retain locomotor capabilities after spinal cord lesions. These results broaden our understanding of animal locomotion and expand our knowledge for the design of robust and modular robots that physically interact with the environment.

Existing belief space motion planning methods are not efficient for underwater robots that are subject to spatially varying motion and sensing uncertainties arising from the non-uniform current disturbances and landmark populations, respectively. Based on a closed-loop stochastic control framework, we propose a fast Gaussian belief space planning approach for coupled optimization of trajectory, localization and control, resulting in a non-linear programming problem (NLP). In particular, as opposed to advancing the covariance by a Kalman filter in the existing literature, we utilize an upper bound of the trace propagation of the covariance, thereby avoiding to solve Riccati equations and thus, reducing the computational complexity. The NLP is then efficiently solved by sequential quadratic programming based on the initial solutions obtained from RRT-connect. These initials lie in multiple homotopy classes guaranteed by H-signature discrimination, leading to global optimality with probability one as the number of samples in RRT-connect goes to infinity. Numerical simulations on holonomic and non-holonomic autonomous underwater vehicles (AUVs) and an Intervention-AUV with a manipulator in cluttered underwater environments demonstrate that optimal and collision-free trajectories with low localization uncertainty are obtained efficiently.

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

Autonomous underwater robots, such as the UX-1 developed in the UNEXMIN project, need to maintain reliable autonomous operation in hazardous and unknown environments. Because of the lack of any kind of real-time communications with a human operated command and control station, the control architecture needs to be enhanced with mission-level self-diagnosis and self-adaptation properties an additional provided by some kind of supervisory or “metacontrol” component to ensure its reliability. In this paper, we propose an ontological implementation of such component based on Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). The solution is based on an ontology of the functional architecture of autonomous robots, which allows inferring the effects of the performance of its constituents components in the functions required during the robot mission, and generate the reconfigurations needed to maintain operation reliably. The concept solution has been validated using a hypothetical set of scenarios implemented in an OWL ontology and an OWLAPI-based reasoner, which we aim at validating by integrating the metacontrol reasoning with a realistic simulation of the underwater robot.

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

In this work, we present the design, implementation, and testing of an attitude control system based on State Feedback Linearization (FL) of a prototype spherical underwater vehicle. The vehicle is characterized by a manifold design thruster configuration for both locomotion and maneuvering, as well as on a novel pendulum-based passive pitch control mechanism. First, the mechanical design and onboard electronics set up of the spherically shaped hull are introduced. Afterward, a high-fidelity dynamic model of the system is derived for a 6 degree-of-freedom (DOF) underwater vehicle, followed by several experiments that have been performed in a controlled environment to compare the performance of the proposed control method to that of a baseline Proportional-Integral-Derivative (PID) controller. Experimental results demonstrate that while both controllers were able to perform the specified maneuvers, the FL controller outperforms the PID in terms of precision and time response., This work was supported by the UNEXMIN project with funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 690008, and has been co-funded by the RoboCity2030-III-CM project (Robotica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and co-funded by Structural Funds of the EU.

Attitude estimation is a crucial aspect for navigation and motion control of autonomous vehicles. This concept is particularly true in the case of unavailability of localization sensors when navigation and control rely on dead reckoning strategies; in this case, indeed, the orientation estimate is also used along with speed measurements to update the position estimate. Among the different approaches proposed in the literature, the de facto state of the art in this field is represented by nonlinear complementary filters: they fuse the measurements of angular rate obtained through gyroscopes, and a measurement of gravity and Earth's magnetic field vectors respectively obtained through accelerometers and magnetometers. This paper is focused on an attitude estimation strategy for autonomous underwater vehicles (AUV). The proposed novelty includes the identification of some critical issues that arise when AUV attitude estimation algorithms are applied in practice. They are mainly due to the use of low-accuracy low-cost microelectromechanical systems (MEMS) sensors and on different sources of magnetic disturbances. Some strategies to overcome the identified issues are proposed, including the integration of a single-axis fiber optic gyroscope (FOG) that ensures a considerable performance improvement with a moderate cost increase. The proposed strategies for detection of issues and sensor fusion have been experimentally tested and validated in a real application scenario estimating the attitude of an AUV performing a lawn mower path. The expected performance improvement is confirmed; the obtained results are described and analyzed in this paper.

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.

Web Ontology Language (OWL) is designed to represent varied knowledge about things and the relationships of things. It is widely used to express complex models and address information heterogeneity of specific domains, such as underwater environments and robots. With the help of OWL, heterogeneous underwater robots are able to cooperate with each other by exchanging information with the same meaning and robot operators can organize the coordination easier. However, OWL has expressivity limitations on representing general rules, especially the statement &ldquo, If &hellip, Then &hellip, Else &hellip, &rdquo, Fortunately, the Semantic Web Rule Language (SWRL) has strong rule representation capabilities. In this paper, we propose a rule-based reasoner for inferring and providing query services based on OWL and SWRL. SWRL rules are directly inserted into the ontologies by several steps of model transformations instead of using a specific editor. In the verification experiments, the SWRL rules were successfully and efficiently inserted into the OWL-based ontologies, obtaining completely correct query results. This rule-based reasoner is a promising approach to increase the inference capability of ontology-based models and it achieves significant contributions when semantic queries are done.

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

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 This work has been partially funded by the Catalan Government (Generalitat de Catalunya) through ACDC grants 2009, 2010, 2011, 2012 and 2013, the EnginyCAT program, MICINN project CTM2010-15216, EU project FP7- ICT-2009-248497 and the UdG (Social Council, VICOROB Research Group, Patronatge of Technical School and Vicerectorate of Research).

Autonomy for robots is one of the key requirement in any field robotic applications. Design and development of autonomous robots raises many challenges to the engineers and full autonomy for robots is still an unfinished job. In this key note address, some of the design challenges and implementation issues will be presented. Along with this, the design of an autonomous underwater robot for surveillance application will be presented as a case study.

We introduce an octopus-inspired, underwater, soft-bodied robot capable of performing waterborne pulsed-jet propulsion and benthic legged-locomotion. This vehicle consists for as much as 80% of its volume of rubber-like materials so that structural flexibility is exploited as a key element during both modes of locomotion. The high bodily softness, the unconventional morphology and the non-stationary nature of its propulsion mechanisms require dynamic characterization of this robot to be dealt with by ad hoc techniques. We perform parameter identification by resorting to a hybrid optimization approach where the characterization of the dual ambulatory strategies of the robot is performed in a segregated fashion. A least squares-based method coupled with a genetic algorithm-based method is employed for the swimming and the crawling phases, respectively. The outcomes bring evidence that compartmentalized parameter identification represents a viable protocol for multi-modal vehicles characterization. However, the use of static thrust recordings as the input signal in the dynamic determination of shape-changing self-propelled vehicles is responsible for the critical underestimation of the quadratic drag coefficient.

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)

This article presents a novel docking system developed for miniature underwater robots. Recent years have seen an increased diffusion of robots for ocean monitoring, exploration and maintenance of underwater infrastructures. The versatility of those vehicles is extremely affected and limited by energetic constraints and difficulties in updating their mission parameters. Submerged docking stations are a promising solution for providing energy sources and data exchange, thus extending autonomy and mission duration of underwater robots. Furthermore, the docking capability is a novel, but promising approach to enable modularity and reconfigurability in underwater robotics. The authors here propose a hybrid docking system composed of a magnetic alignment unit and a mechanical connection. The former passively aligns and guides the underwater vehicle facilitating a subsequent mechanical connection. The reliability of the system is both analytically investigated and experimentally validated. Finally, the mechanical design of the docking system of two miniature underwater robots is described in detail.

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.

This paper presents a methodology for localizing an autonomous tethered underwater robotic vehicle deployed for aquaculture inspection operations. The developed methodology is based on an Asynchronous Unscented Kalman Filer (UKF) to fuse information from onboard sensors along with a'priori knowledge about the aquaculture's geometry and the underwater robot's hydrodynamics. The performance of the proposed methodology is assessed through accuracy and consistency metrics generated from simulation benchmarks.

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

Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Summarization: A novel cooperative controller design for autonomous underwater vehicles is proposed, implemented and tested. The design procedure follows the basic principles of behaviour-based systems to create two different biomimetic roles, encapsulating the characteristics of an extremely rare cooperative underwater predator behaviour found in the wild: bottlenose dolphins group-hunting with division of labour and role specialization. The behaviour-based model is comprised of an hierarchy with different levels of competence, interaction and intercommunication between several behaviour modules. Two distinct, cooperating roles mimicking the driver and the non-driving or barrier members of a hunting bottlenose dolphins group emerged from the behaviour-based subsumption architecture controller designation. This behaviour-based cooperation exploits the driver’s individual capability, in fact a physical gift, of initializing, coordinating a hunting bout, detecting and herding the school of fish along with the contribution of non-driving dolphins ability to comprehend and follow the driver’s master plan and thus act as barriers for the fish trying to escape. Both roles are programmed to act upon sensory information regarding the robot’s environment, provided by a vision sensor module and an inertial measurement unit. The vision sensor detects colour light targets, classifies them according to the experimentation scenario and triggers behaviours’ interaction. The inertial measurement unit supports behaviours’ navigation and guidance necessities. Controller testing, under several simulated scenarios, proved the reliability and modular functionality of the cooperative behaviour-based model and its potential for supporting the autonomy of underwater robotic vessels commissioned in oceanography, environmental monitoring and exploration, serving tasks that can easily be seen as an extent of dolphins’ group hunting. Apart from the simulation, the same behaviour-based controller was tested in real world, with a prototype autonomous vessel. In this case, due to certain limitations of the experimental apparatus, the behaviour-based controller implemented an individual biomimetic role inspired by the real life routines of wandering, hunting, feeding, hiding and nesting exercised by underwater creatures. The individual role, behaviour-based controller was an effort to approach the sea creatures’ autonomy, observed macroscopically as an inevitable iteration and commutation of distinct behaviour modules, guided by the overall objective of staying alive. The prototype robot was commissioned as an experimentation platform for testing the framework of autonomous behaviour-based controllers and materialize the biomimetic metaphor between the maritime environment and a laboratory experimentation area of 1m3 . Περίληψη: Σκοπός της διατριβής είναι η ανάδειξη συνεργατικής συμπεριφοράς από μια ομάδα Αυτόνομων Υποβρύχιων Ρομποτικών Σκαφών. Για το λόγο αυτό σχεδιάστηκε, κατασκευάστηκε και εξελίχθηκε ένα πρωτότυπο ρομποτικό σκάφος χαμηλού κόστους. Επίσης, εγκαταστάθηκε εντός εργαστηριακού χώρου ο κατάλληλος εξοπλισμός για υποβρύχιο πειραματισμό. Η αξιοπλοΐα του πρωτότυπου σκάφους δοκιμάστηκε μεθοδικά με πειράματα που αφορούσαν τον έλεγχο της γωνίας παρέκκλισης του σκάφους και τη δυνατότητά του να ακολουθεί ένα κινούμενο φωτεινό στόχο. Ως αποτέλεσμα αυτού του πειραματισμού, αναπτύχθηκε η κατάλληλη αρχιτεκτονική λογισμικού- υλικού του ρομπότ, επί της οποίας υλοποιήθηκαν ο αντίστοιχος αναλογικός- διαφορικός ελεγκτής και ελεγκτής ασαφούς λογικής. Ο πειραματισμός απέδειξε, σε πρώτη φάση, την αποτελεσματικότητά των ελεγκτών και της σχεδίασης του ρομποτικού σκάφους. Στη συνέχεια, χρησιμοποιώντας την ίδια αρχιτεκτονική λογικού υλικού του ρομπότ, εφαρμόστηκε έλεγχος αλληλοεξαρτώμενων συμπεριφορών. Σχεδιάστηκε ένα μοντέλο τριών ιεραρχημένων επιπέδων για την επίτευξη μιας ατομικής βιομιμητικής συμπεριφοράς, καθ' ομοίωση των βασικών συμπεριφορών που συναντώνται στα έμβια υποβρύχια όντα: περιπλάνηση, αναζήτηση τροφής, αποφυγή θηρευτών και αναζήτηση φωλιάς. Αυτό το μοντέλο ελέγχου, αφού απέδειξε κατά τη διάρκεια δοκιμών στο χώρο πειραματισμού την αποτελεσματικότητά και την αξιοπιστία του, αποτέλεσε τη βάση για το σχεδιασμό μιας βιομιμητικής συνεργατικής συμπεριφοράς για ομάδα υποβρύχιων ρομπότ. Τα μέλη της ομάδας διακρίνονται σε δύο ρόλους, του αρχηγού και των ακολούθων του και παρουσιάζουν, συνολικά, την υλοποίηση της θηρευτικής τεχνικής που έχει παρατηρηθεί στην οικογένεια των ρινοδέλφινων. Κάθε ρόλος υποστηρίζεται από το αντίστοιχο μοντέλο αλληλοεξαρτώμενων συμπεριφορών. Με τον τρόπο αυτό υλοποιήθηκε η περιπλάνηση του θηρευτή αρχηγού και η συνοδεία του από τους ακόλουθούς του, ο αλληλοεντοπισμός μεταξύ των μελών της ομάδας, η αναζήτηση θηραμάτων και η επίθεση σε αυτά. Οι δύο βιομιμητικοί ρόλοι υλοποιήθηκαν με τη βοήθεια λογισμικού προσομοίωσης. Οι προσομοιωμένες δοκιμές απέδειξαν την αποτελεσματική συνεργασία μεταξύ των μελών μιας ομάδας ρομπότ, πανομοιότυπων με το πρωτότυπο που κατασκευάστηκε.

IROS 2013: New Horizon Conference Digest, ISBN:978-1-4673-6357-0, ISBN:978-1-4673-6356-3, ISBN:978-1-4673-6358-7

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

In this paper we present a Control Moment Gyroscope (CMG) for underwater robots. This is a single gimbal CMG with pyramid type configuration. This device has a modular design and is self-contained (i.e., all mechanical and electrical parts are contained in the CMG's hull.) The mechanical, electrical and electronic components of the CMG are described, and two experimental test are carry out to demonstrate the system functionality. © 2011 IEEE.

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 present details and results obtained with an underwater system comprising two different autonomous underwater robots (AUV) and ten static underwater nodes (USN) networked together optically and acoustically. The AUVs can locate and hover above the static nodes for data upload, and they can perform network maintenance functions such as deployment, relocation, and recovery. The AUVs can also locate each other, dock, and move using coordinated control that takes advantage of each AUV’s strength.

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.

Autonomous Underwater Vehicles (AUVs) are now being introduced into the fleet to improve Mine Warfare capabilities. Several AUVs are under government-contracted development. Mission planning and data reporting vary between vehicles and systems. This variance does not pose an immediate problem, as only one AUV is currently in production. However, as more AUVs are put into production, commands will begin to get multiple AUVs. Without a single mission command language, multiple systems will require familiarity with multiple languages. Extensible Markup Language (XML) and related technologies may be used to facilitate interoperability between dissimilar AUVs and extract and integrate mission data into Navy C4I systems. XML makes archive maintenance easier, XML documents can be accessed via an http server, and, in root form, XML is transferable on the fly by stylesheet. This thesis presents an XML-based mission command for the command and control of AUVs. In addition, this thesis discusses XML technology and how XML is a viable means of achieving interoperability. Furthermore, this thesis provides an example mission file using existing software, and demonstrates the future of XML in AUV technology. Finally, this work ends with a compelling argument for the use of an XML-based mission command language to command all AUVs. http://archive.org/details/anxmlbasedmissio10945975 Ensign, United States Navy Captain, United States Air Force Approved for public release; distribution is unlimited.

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”

Bio-inspired underwater robots have several benefits compared to traditional underwater vehicles such as agility, efficiency, and environmentally friendly body. However, bio-inspired underwater robots developed so far have a single swimming mode, which may limit their capability to perform different tasks. This paper presents a re-configurable bio-inspired underwater robot that can change the morphology to enable multiple swimming modes: octopus-mode and fish-mode. The robot is 60 cm long and 50 cm wide, weighing 2.1 kg, and consists of a re-configurable body and 8 compliant arms that are actuated independently by waterproof servomotors. In the robot, the octopus-mode is expected to perform unique tasks such as object manipulation and ground locomotion as demonstrated in literature, while the fish-mode is promising to swim faster and efficiently to travel long distance. With this platform, we investigate the effectiveness of adaptive morphology in bio-inspired underwater robots. For this purpose, we evaluated the robot in terms of the cost of transport and the swimming efficiency of both the morphologies. The fish-mode exhibited a lower cost of transport of 2.2 and higher efficiency of 1.2 % compared to the octopus-mode, illustrating the effect of the multiple swimming modes by adaptive morphology.

Dielectric elastomer actuators (DEAs), a soft actuator technology, hold great promise for biomimetic underwater robots. The high-voltages required to drive DEAs can however make them challenging to use in water. This paper demonstrates a method to create DEA-based biomimetic swimming robots that operate reliably even in conductive liquids. We ensure the insulation of the high-voltage DEA electrodes without degrading actuation performance by laminating silicone layers. A fish and a jellyfish were fabricated and tested in water. The fish robot has a length of 120 mm and a mass of 3.8 g. The jellyfish robot has a 61 mm diameter for a mass of 2.6 g. The measured swimming speeds for a periodic 3 kV drive voltage were ∼8 mm/s for the fish robot, and ∼1.5 mm/s for the jellyfish robot.