This thesis deals with the Simultaneous Localisation and Mapping algorithm as it pertains to the deployment of mobile systems in unknown environments. Simultaneous Localisation and Mapping (SLAM) as defined in this thesis is the process of concurrently building up a map of the environment and using this map to obtain improved estimates of the location of the vehicle. In essence, the vehicle relies on its ability to extract useful navigation information from the data returned by its sensors. The vehicle typically starts at an unknown location with no a priori knowledge of landmark locations. From relative observations of landmarks, it simultaneously computes an estimate of vehicle location and an estimate of landmark locations. While continuing in motion, the vehicle builds a complete map of landmarks and uses these to provide continuous estimates of the vehicle location. The potential for this type of navigation system for autonomous systems operating in unknown environments is enormous. One significant obstacle on the road to the implementation and deployment of large scale SLAM algorithms is the computational effort required to maintain the correlation information between features in the map and between the features and the vehicle. Performing the update of the covariance matrix is of O(n�) for a straightforward implementation of the Kalman Filter. In the case of the SLAM algorithm, this complexity can be reduced to O(n�) given the sparse nature of typical observations. Even so, this implies that the computational effort will grow with the square of the number of features maintained in the map. For maps containing more than a few tens of features, this computational burden will quickly make the update intractable - especially if the observation rates are high. An effective map-management technique is therefore required in order to help manage this complexity. The major contributions of this thesis arise from the formulation of a new approach to the mapping of terrain features that provides improved computational efficiency in the SLAM algorithm. Rather than incorporating every observation directly into the global map of the environment, the Constrained Local Submap Filter (CLSF) relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment. This representation is shown to reduce the computational complexity of maintaining the global map estimates as well as improving the data association process by allowing the association decisions to be deferred until an improved local picture of the environment is available. This approach also lends itself well to three natural extensions to the representation that are also outlined in the thesis. These include the prospect of deploying multi-vehicle SLAM, the Constrained Relative Submap Filter and a novel feature initialisation technique. Results of this work are presented both in simulation and using real data collected during deployment of a submersible vehicle equipped with scanning sonar.

The accurate prediction of forces and motions on autonomous underwater vehicles (AUVs) operating close to the wavy free surface is imperative to their usefulness as oceanic research and warfare craft. Maneuvering models for underwater vessels are typically constrained to deep water motions where surface effects are negligible; however, a number of modeling assumptions that are applicable for deep water motions become invalid when the vessel is in proximity to the air-water interface. This dissertation investigates several aspects for the inclusion of free surface effects in maneuvering predictions of a shallowly submerged underwater vehicle. A lumped parameter maneuvering model for deeply submerged motion is improved to accommodate depth dependent effects by updating hydrodynamic derivatives using strip theory and boundary element method analysis. This new model can predict near-surface maneuvering motions of an AUV operating in calm or wavy waters. Alternative free surface affected motion predictions are offered by the Lagrangian Nonlinear Maneuvering and Seakeeping (LNMS) model, which provides motion predictions of a vehicle under waves using calculations from first principle energy considerations. While both models provide their own approach to shallowly submerged vehicle motion predictions, each model suffers from its own limiting hydrodynamic modeling assumptions such as linearized free surface boundary conditions, potential flow assumptions, and slowly varying motions. An investigation into the errors from these simplifying assumptions, including under prediction of the steady-state wave making forces and neglect of viscous effects, led to the creation of an innovative impulse motion model for the calculation of hydrodynamic parameters reducing the need for simplifying assumptions. The significant, novel contributions to near-surface AUV maneuvering research provided in this dissertation are listed below: 1. Creation of a free-surface affected lumped parameter maneuvering and seakeeping model using depth corrected hydrodynamic parameters from strip theory and boundary element method analysis 2. Investigation into the errors associated with linearized free surface boundary conditions and potential flow assumptions during the prediction of near-surface steady-state motions 3. Development of an impulse motion simulation procedure using 3D Unsteady Reynolds- Averaged Navier-Stokes Equation (URANSE) solvers to calculate the infinite frequency hydrodynamic added mass of a shallowly submerged underwater vehicle from rest and constant forward speed / Doctor of Philosophy / Autonomous underwater vehicles (AUVS) are an increasingly used tool in the exploration, defense, and study of our oceans and seaways. An essential aspect for the creation of various AUV systems is the accurate prediction of forces and motions while operating in a variety of different conditions, including near the wavy water surface. Maneuvering models that predict the motions of underwater vehicles often opt for deep water simplifying assumptions where the free surface has no effect; however, these assumptions aren't always valid. This dissertation looks to better understand the effects that a free surface has on AUV motion predictions and how these effects can be captured, understood, and incorporated within different maneuvering models. This goal is achieved by updating a previously constructed deep water maneuvering model to account for proximity to the free surface as well as exploring new methods that calculate the hydrodynamic parameters of a vehicle operating at these depths. With these findings, AUVs will be better informed to move as intended while operating in important combat and research zones of the ocean.

This thesis describes the challenges involved in detecting sources of acoustic noise using an autonomous underwater vehicle (AUV) in real world environments. The initial part of this thesis describes the developments made for redesigning an acoustic sensing system that can be used to estimate the relative bearing between a source of acoustic noise and an AUV. With an estimate of the relative bearing, the AUV can maneuver toward the source of noise. The class of algorithms that are used to estimate bearing angle are known as beamforming algorithms. A comparison of the performance of a variety of beamforming algorithms is presented. When estimating the bearing to a source of noise from a small AUV, the noise of the AUV, especially its propulsor, pose significant challenges. Toward the goal of active cancellation of AUV self-noise, we propose placing an additional hydrophone inside the AUV in order to estimate the AUV self-noise that appears on the exterior hydrophones that are used for bearing estimation. / Master of Science / A real world application using an autonomous underwater vehicle (AUV) is presented in this thesis. The application deals with detecting and estimating the relative location (bearing angle) between sources of acoustic noise and the AUV. The thesis starts by describing design changes made to target data sensing system inside the AUV for collecting and estimating the bearing angle. The estimation of bearing angle is done with a class of algorithms called beamforming algorithms whose performance comparison is presented on real world data. Operating the AUV propulsor yields inaccurate bearing angle estimations and thus presents a huge challenge for bearing estimation. We propose measuring AUV self-noise using additional sensors to move towards the goal of cancelling AUV self-noise and recovering target signal for accurate bearing estimation.

The goal of this design process was to achieve the most efficient propulsive system for the candidate autonomous underwater vehicle (AUV) as possible. A mathematical approach, using fundamental motor equations and derived quantities, was used to characterize and select an efficient brushless electric motor for the propulsion system. A program developed at MIT, Massachusetts Institute of Technology, called OpenProp versions 1 and 2.3 was utilized to design a custom propeller that maximizes the efficiency of the system. A brushless electric motor was selected for the candidate AUV based on a survey of available off the shelf motors and a mathematical characterization process. In parallel with the motor characterization a propeller design was optimized using OpenProp v1 to perform a parametric analysis. OpenProp v2.3 was then used to design a unique propeller for the selected motor. The propeller design resulted in a final propeller with an efficiency of 79.93%. The motor characterization process resulted in two candidate motors being selected, the NeuMotor 1925-3Y and NeuMotor 1521-10.5Y, for in house testing and evaluation. A total propulsive system efficiency of between 44% and 46% was achieved depending on which motor is selected for the final design. / Master of Science

The Virginia Tech self-mooring autonomous underwater vehicle (AUV) is capable of mooring itself on the seafloor for extended periods of time. The AUV is intended to travel to a desired mooring location, moor itself on the seafloor, and then release the mooring and return to a desired egress location. The AUV is designed to be an inexpensive sensor platform. The AUV utilizes a false nose that doubles as an anchor. The anchor is neutrally buoyant when attached to the AUV nose. When the vehicle moors it releases the false nose, which floods the anchor making it heavy, sinking both the anchor and AUV to the seafloor. At the end of the mooring time the vehicle releases the anchor line and travels to the recovery location. A prototype vehicle was constructed from a small-scale platform known as the Virginia Tech 475 AUV and used to test the self-mooring concept. The final self-mooring AUV was then constructed to perform the entire long duration mission. The final vehicle was tested successfully for an abbreviated mission profile. This report covers the general design elements of the self-mooring AUV, the detailed design of both the prototype and final AUVs, and the results of successful field trials with both vehicles. / Master of Science

Cette thèse étudie le problème de la localisation et de la cartographie simultanée (SLAM), dans des environnements non structurés, c'est-à-dire, qui ne peuvent pas être décrits par des équations ou des formes géométriques. Ces types d'environnements sont souvent rencontrés dans le domaine sous-marin. Contrairement aux approches classiques, l'environnement n'est pas modélisé par une collection de descripteurs ou d'amers ponctuels, mais directement par des ensembles. Ces ensembles, appelés forme ou shape, sont associés à des caractéristiques physiques de l'environnement, comme par exemple, des textures, du relief ou, de manière plus symbolique, à l'espace libre autour du véhicule. D'un point de vue théorique, le problème du SLAM, basé sur des formes, est formalisé par un réseau de contraintes hybrides dont les variables sont des vecteurs de Rn et des sous-ensembles de Rn. De la même façon que l'incertitude sur une variable réelle est représentée par un intervalle de réels, l'incertitude sur les formes sera représentée par un intervalle de forme. La principale contribution de cette thèse est de proposer un formalisme, basé sur le calcul par intervalle, capable de calculer ces domaines. En application, les algorithmes développés ont été appliqués au problème du SLAM à partir de données bathymétriques recueillies par un véhicule sous-marin autonome (AUV). / This thesis deals with the simultaneous localization and mapping (SLAM) problem in unstructured environments, i.e. which cannot be described by geometrical features. This type of environment frequently occurs in an underwater context.Unlike classical approaches, the environment is not described by a collection of punctual features or landmarks, but directly by sets. These sets, called shapes, are associated with physical features such as the relief, some textures or, in a more symbolic way, the space free of obstacles that can be sensed around a robot. In a theoretical point of view, the SLAM problem is formalized as an hybrid constraint network where the variables are vectors and subsets of Rn. Whereas an uncertain real number is enclosed in an interval, an uncertain shape is enclosed in an interval of sets. The main contribution of this thesis is the introduction of a new formalism, based on interval analysis, able to deal with these domains. As an application, we illustrate our method on a SLAM problem based on bathymetric data acquired by an autonomous underwater vehicle (AUV).

L'utilisation de correcteur discret à période d'échantillonnage variable peut être intéressante dans plusieurs cas, par exemple lorsque la mesure, bien qu'envoyée de façon périodique, est reçue à intervalle variable. C'est le cas en milieu marin lorsque la mesure d'altitude est effectuée avec un capteur à ultrason (la durée du trajet du signal dans l'eau dépend de la distance par rapport au fond). Le délai variable entre deux réceptions de mesures, peut être vu comme une variation de période d'échantillonnage pour le contrôleur. La synthèse de lois de commande discrète à période d'échantillonnage variable a déjà été étudiée pour des systèmes stationnaires. On se propose ici d'étendre cette méthode pour des systèmes Linéaires à Paramètres Variants (LPV), qui permettent de conserver des paramètres importants d'un système non-linéaire en temps que paramètres d'un système linéaires. La synthèse de contrôleur repose sur le méthodologie H∞, appliquée aux systèmes LPV. En particulier, on s'intéressera à deux approches existantes dans la littérature : l'approche polytopique (où le paramètre variant évolue dans un volume convexe) et la Représentation Linéaire Fractionnelle (LFR). La méthode proposée est appliquée au contrôle d'un AUV (Autonomous Underwater Vehicle), qui est système difficile à contrôler du fait d'importantes non-linéarités. Des résultats de simulations permettront de montrer l'intérêt de la méthode pour le contrôle d'altitude d'un AUV, et notamment les améliorations apportées par l'ajout de paramètres issus du système non-linéaire au modèle utilisé pour la synthèse des régulateurs. / Discrete time controller using variable sampling can ba interesting in several cases, for axample when the measure, even if send periodically, is received with a variable interval. This is the case in submarine environement, when the altitude measurement is done using an ultrasonic sensor. Discrete control laws synthesis with variable sampling period have already been studied for LTI systems. The results are here extended to Linear Parameter Varying systems, that allow to keep some non-linearities as parameters of a linear system. In particular, two approaches are investigated : the polytopic and the LFR. The proposed method is applied for the altitude control of an autonomous underwater vehicle (AUV). Simulations results will show the interest of the method, in particular how results are improved by adding some parameters coming from the non linear model.

L’utilisation des AUV pour une exploitation durable des ressources océaniques est pertinente. Un robot sous-marin peut être utilisé comme plateforme pour observer, recueillir des informations sur l’environnement marin. Afin d’améliorer la qualité des observations et d’augmenter la capacité de navigation, de nombreuses questions doivent être abordées et examinées simultanément. Nous abordons ici le problème du pilotage de ces robots autonomes.Atteindre la maniabilité nécessaire dépend de deux facteurs clés: un modèle hydrodynamique précis et un système de contrôle performant. Cependant, le coût de développement d’un modèle précis est généralement très élevé. De plus, lorsque la géométrie du robot est complexe, il devient très difficile d’identifier de manière pertinente les paramètres dynamiques et hydrodynamiques. En outre, du point de vue de la commande, les modèles obtenus sont non linéaire, en particuliers pour les amortissements.De nombreux phénomènes dynamiques ne sont pas modélisés: dynamiques internes au robot, environnementales, liées aux bruits des capteurs, aux retards intrinsèques. Dans les concours de robotique sous-marine, il est confirmé que le traditionnel régulateur Proportionnel-Intégral-Dérivé (PID) est peu efficace pour les robots légers. Dans ce cas, notre champ d’application est plus axé sur la combinaison des approches de modélisation numérique et la commande robuste.Dans ce travail, nous proposons un schéma de régulation basé sur la commande robuste et la modélisation. La régulation robuste a été mise en place et validée en mer sur un AUV de la marque CISCREA et la solution proposée utilise Computational Fluid Dynamic (CFD) pour caractériser les deux paramètres hydrodynamiques (matrice de masse ajoutée et matrice d’amortissement). Puis un modèle à quatre degrés de liberté est construit pour le CISCREA. Les résultats numériques et expérimentaux sont alors comparés.La commande robuste proposée est basée sur une compensation non linéaire et de la commande H∞. La validation de la robustesse a été testée par simulation en Matlab et finalement validée par des essais en mer à Brest. La simulation et l’expérience montrent que l’approche en plus d’être robuste est plus rapide que les régulateurs précédemment proposés. / Autonomous Underwater Vehicle (AUV) is a relevant technology for the sustainable use of ocean resources. AUV can be used as an important ocean observing platform to collect information on marine environmental characteristics for research and industry fields. In order to improve the observation quality and increase the navigation ability, many issues should be addressed and considered simultaneously. Achieve necessary maneuverability depends on two key factors: an accurate hydrodynamic model and an advanced control system. However, the cost to develop an accurate hydrodynamic model, which shrinks the uncertainty intervals, is usually high. Meanwhile, when the robot geometry is complex, it becomes very difficult to identify its dynamic and hydrodynamic parameters. In addition, according to the quadratic damping factor, underwater vehicle dynamic and hydrodynamic model is nonlinear from the control point of view. Moreover, unmodeled dynamics, parameter variations and environmental disturbances create significant uncertainties among the nominal model and the reality. Sensor noise, signal delay as well as unmeasured states also affect the stability and control performance of the motion control system. In many of our underwater competitions, it has been confirmed that the traditional Proportional-Integral-Derivative (PID) regulation is less efficient for low mass AUV. In this case, our scope is more focused on the combination of numerical modeling approaches and robust control schemes. In this work, we proposed a model based robust motion control scheme. Without loss of generality, a robust heading controller was implemented and validated in the sea on cubic-shaped CISCREA AUV. The proposed solution uses cost efficient Computational Fluid Dynamic (CFD) software to predict the two hydrodynamic key parameters: The added mass matrix and the damping matrix. Four Degree of Freedom (DOF) model is built for CISCREA from CFD calculation. Numerical and experimental results are compared. Besides, the proposed control solution inherited the numerically obtained model from previous CFD calculation. Numerically predicted the actuator force compensates the nonlinear damping behavior result in a linear model with uncertainties. Based on the bounded linear nominal model, we proposed H∞ approach to handle the uncertainties, we used kalman filter to estimate unmeasured states such as angular velocity and we developed smith compensator to compensate the sensor signal delay. The proposed robust heading control application uses only one compass as feedback sensor. This is important while AUV is working at certain depth where only magnetic sensors still work. Our robust control scheme was simulated in Matlab and validated in the sea near Brest. Simulation shows obvious advantage of the proposed robust control approach. Meanwhile, the proposed robust heading control is much faster than PID controller. The robust controller is insensitive to uncertainties and has no overshot. From both simulations and real sea experiments, we found our proposed robust control approach and the one compass heading control applications are efficient for low mass and complex-shaped AUV CISCREA.

In this thesis, we introduce a Rao-Blackwellized Particle Filter (RBPF) for the algorithm Simultaneously Localizing and Mapping (SLAM) to be used on an Autonomous Underwater Vehicle (AUV) with a Stochastic Variational Gaussian Process (SVGP) algorithm. With a positive result, the combination was proven to be working. The main limitation has been the complexity of the two algorithms. Even though we got the two working together in a dynamic environment, it has only worked in a simulation. Before testing the solution on a real AUV in a natural environment, modifications need to be added, speeding up the whole process. / I det här examensarbetet har vi introducerat ett Rao-Blackwellized Partikel Filter (RBPF) med lokaliserings och kartläggnings algoritmen (SLAM). Detta för att användas på en autonom undervattensfarkost (AUV), tillsammans med algoritmen för att förutspå hittills osedda platser (SVGP). Kombinationen av de två algoritmerna på farkosten visade sig fungera. Den största begränsningen har varit hur tunga de båda algoritmerna är, vilket har lett till att färre partiklar har kunnat användas och med mindre noggrann träning per partikel. Dessutom har resultaten endast visats i en simulerad miljö. Innan det blir möjligt att testa kombinationen i en verklig miljö måste modifikationer göras för att snabba på träningen av algoritmerna och på så sett kunna använda sig av fler partiklar.

One challenge for Autonomous Underwater Vehicle (AUV) multibeam surveying is the limited ability to assess internal vertical agreement rapidly and reliably. Applying an external ellipsoid reference to AUV multibeam data would allow for field comparisons. A method is established to merge ellipsoid height (EH) data collected by a surface vessel in close proximity to the AUV. The method is demonstrated over multiple collection missions in two separate areas. Virtual tide corrector values are derived using EH data collected by a boat and a measured ellipsoid to chart datum separation distance. Those values are compared to measurements by a traditional tide gauge installed nearby. Results from the method had a mean difference of 6 centimeters with respect to conventional data and had a mean total propagated uncertainty of 15 centimeters at the 95% confidence interval. Methodologies are examined to characterize their accuracies and uncertainty contribution to overall vertical correction.