This thesis proposes a method to simulate the dynamics of an autonomous underwater vehicle towing another autonomous underwater vehicle of equivalent size using a marine cable in the vertical and horizontal plane. There is a coupling effect between the two vehicles because the towed vehicle is of equivalent size. This means that the towed vehicle cannot be modeled as just a payload but rather, must incorporate the forces and moments experienced and acting on it. In this work, only AUVs with symmetrical hulls are considered, where the towing AUV is moving at a constant velocity with a set thrust while the towed AUV has no thrust. The rope system is another important component that needs to be modeled correctly because the rope material and type significantly impact the motion of the vehicles. The rope system in this study is modeled using a numerical approach called the lumped mass spring damper method which is easy to understand and computationally inexpensive. The rope model accounts for buoyancy differences in different ropes and permits cable flexibility. This thesis enables us to study the motion of multiple combinations of different ropes and axi-symmetric types of underwater vehicles with any fixed or movable fin configuration. / M.S. / This thesis studies the motion of an autonomous underwater vehicle towing another autonomous underwater vehicle which is a large as it is. The towed vehicle cannot be assumed to be just a mass attached to the towing vehicle. There is an interaction between the two vehicle. The towed vehicle places a force on the towed vehicle and the towed vehicle likewise places a force on the towing vehicle. This interaction needs to be modeled correctly to fully capture the impact of both vehicles and their appendages. Additionally, the rope system poses a huge impact on the two vehicle depending on what type of rope is selected. Multiple factors affect the performance of a rope such as the shape and the elasticity. Some ropes may also be denser due to their material type and are less buoyant than others. These factors are considered in the modeling of the overall system and allows us to study different combinations of ropes and symmetric hulled autonomous underwater vehicles.

Precise navigation of autonomous underwater vehicles (AUV) is one of the most important challenges in the realization of distributed and cooperative algorithms for marine applications. We investigate an underwater navigation technology that enables an AUV to compute its trajectory in the presence of unknown currents in real time and simultaneously estimate the currents, using range or distance measurements from a single known location. This approach is potentially useful for small AUVs which have severe volume and power constraints. The main contribution of this work is observability analysis of the proposed navigation system using novel approaches towards uniform observability of linear time-varying (LTV) systems. We utilize the notion of limiting systems in order to address uniform observability of LTV systems. Uniform observability of an LTV system can be studied by assessing finite time observability of its limiting systems. A new definition of uniform observability over a finite interval is introduced in order to address existence of an observer whose estimation error is bounded by an exponentially decaying function on the finite interval. We also show that for a class of LTV systems, uniform observability of a lower dimensional subsystem derived from an LTV system is sufficient for uniform observability of the LTV system. / Ph. D.

This dissertation addresses high-level path planning and cooperative control for autonomous vehicles. The objective of our work is to closely and rigorously incorporate classication and detection performance into path planning algorithms, which is not addressed with typical approaches found in literature. We present novel path planning algorithms for two different applications in which autonomous vehicles are tasked with engaging targets within a stochastic environment. In the first application an autonomous underwater vehicle (AUV) must reacquire and identify clusters of discrete underwater objects. Our planning algorithm ensures that mission objectives are met with a desired probability of success. The utility of our approach is verified through field trials. In the second application, a team of vehicles must intercept mobile targets before the targets enter a specified area. We provide a formal framework for solving the second problem by jointly minimizing a cost function utilizing Bayes risk. / Ph. D.

This thesis presents the derivation of the dynamic model of an autonomous underwater vehicle that tows a large payload. Our analysis is motivated by the fact that the payload is so large that it cannot be modeled by simply appending its dynamics to the dynamics of the autonomous underwater vehicle. Hence, the coupling between the vehicle and payload must be fully modeled. Furthermore, several approximation techniques based on analytic and empirical formulations are investigated for computing the hydrodynamic coefficients of the vehicle. Efficacy and limitations of the approximation techniques are assessed by comparison with hydrodynamic coefficients that are estimated using high-fidelity computational fluid dynamics simulations. / Master of Science / This thesis presents the model to used to predict the motion of an autonomous underwater vehicle that tows a large object. Our analysis is motivated by the fact that the size of the object is so large that it will have a substantial impact on the motion of the vehicle, and likewise the vehicle will have a substantial impact on the object, requiring that the interaction between the two bodies to be fully modeled. The fluid forces and moments acting on the vehicle are approximated using techniques from hydrodynamic theory and experimental results. The accuracy of the approximation is assessed by comparing of the estimated forces and moments with those seen in high-fidelity simulations.

In this dissertation, we seek to improve collision avoidance for autonomous underwater vehicles (AUVs). More specifically, we consider the case of a small AUV using a forward-looking sonar system with a limited number of beams. We describe a high-fidelity sonar model and simulation environment that was developed to aid in the design of the sonar system. The simulator achieves real-time visualization through ray tracing and approximation, and can be used to assess sonar design choices, such as beam pattern and beam location, and to evaluate obstacle detection algorithms. We analyze the benefit of using a few beams instead of a single beam for a low-cost obstacle avoidance sonar for small AUVs. Single-beam systems are small and low-cost, while multi-beam sonar systems are more expensive and complex, often incorporating hundreds of beams. We want to quantify the improvement in obstacle avoidance performance of adding a few beams to a single-beam system. Furthermore, we developed a collision avoidance strategy specifically designed for the novel sonar system. The collision avoidance strategy is based on posterior expected loss, and explicitly couples obstacle detection, collision avoidance, and planning. We demonstrate the strategy with field trials using the 690 AUV, built by the Center for Marine Autonomy and Robotics at Virginia Tech, with a prototype forward-looking sonar comprising of nine beams. / Doctor of Philosophy / This dissertation focuses on improving collision avoidance capabilities for small autonomous underwater vehicles (AUVs). Specifically, we are looking at the scenario of an AUV equipped with a forward-looking sonar system using only a few beams to detect obstacles in our environment. We develop a sophisticated sonar model and simulation environment to facilitate the design of the sonar system. Our simulator enables real-time visualization, offering insights into sonar design aspects. It also serves as a tool for evaluating obstacle detection algorithms. The research investigates the advantages of utilizing multiple beams compared to a single-beam system for a cost-effective obstacle avoidance solution for small AUVs. Single-beam sonar systems are small and affordable, while multi-beam sonar systems are more complex and expensive. The aim is to quantify the improvement in obstacle avoidance performance when adding additional sonar beams. Additionally, a collision avoidance strategy tailored to the novel sonar system is developed. This strategy, developed using a statistical model, integrates obstacle detection, collision avoidance, and planning. The effectiveness of the strategy is demonstrated through field trials using the 690 AUV, constructed by the Center for Marine Autonomy and Robotics at Virginia Tech, equipped with a prototype forward-looking sonar using nine beams.

O ambiente aquático tem notória importância para a pesquisa, pela biodiversidade e vastidão, e também do ponto de vista comercial, para a indústria militar e de óleo&gás por exemplo. Entretanto, a sua exploração é prejudicada por diversos fatores, entre eles devido à dificuldade de navegação. Infelizmente, carece-se de sinal GPS (Global Positioning System) embaixo d\'água, o que exige outras técnicas de localização. Assim, este trabalho analisa um sistema de navegação para um veículo submarino autônomo. Graças a sensores de velocidade, girômetros, bússola, entre outros, aplica-se o princípio de dead reckoning para calcular a posição atual do veículo a partir da última posição conhecida. Para tal, é feito inicialmente um estudo dos sensores a serem utilizados e um algoritmo de navegação é proposto, cujos resultados são expressos em coordenadas geodésicas (latitude e longitude), permitindo a visualização da trajetória do veículo em mapas geo-referenciados. Além disso, problemas práticos de medição são tratados. Em seguida, é feito um estudo sobre o ruído dos sensores, utilizando a curva de variância de Allan para caracterização dos sinais dos girômetros e do DVL (Doppler Velocity Logger). Por meio de equações de propagação de erro, os ruídos são recuperados em simulação, permitindo a estimação do erro de posição e de atitude (posição angular) acumulados para uma dada manobra. Finalmente, discute-se um critério de emersão a partir das estimativas de erro de posição. / The main part of our planet is filled with water, so the aquatic environment has notorious research and commercial importance. However, its exploration faces many difficulties. In navigation, the lack of GPS signal (Global Positioning System) during underwater missions requires different techniques, so this document focus on analyzing a navigation system for autonomous underwater vehicles. Thanks to different embedded sensors, like DVL (Doppler Velocity Logger), compass, gyrometers and others, the processes of dead reckoning is applied, witch calculates vehicle\'s current position by using the previously determined position. To do so, a navigation algorithm is implemented, providing geodesic coordinates to plot vehicle\'s trajectories on geo-referenced maps. Also, practical difficulties are discussed and treated. To improve the quality of the results, girometer\'s and DVL\'s errors are analyzed using Allan\'s variance and the navigation errors are estimated using first order time derivative equations in an augmented state space. Lastly, it is discussed a criterion to emerge and correct the vehicle\'s position using GPS signal.

The goal of Evolutionary Robotics (ER) is the development of automatic processes for the synthesis of robot control systems using evolutionary computation. The idea that it may be possible to synthesise robotic control systems using an automatic design process is appealing. However, ER is considerably more challenging and less automatic than its advocates would suggest. ER applies methods from the field of neuroevolution to evolve robot control systems. Neuroevolution is a machine learning algorithm that applies evolutionary computation to the design of Artificial Neural Networks (ANN). The aim of this thesis is to assay the practical characteristics of neuroevolution by performing bulk experiments on a set of Reinforcement Learning (RL) problems. This thesis was conducted with the view of applying neuroevolution to the design of neurocontrollers for small low-cost Autonomous Underwater Vehicles (AUV). A general approach to neuroevolution for RL problems is presented. The is selected to evolve ANN connection weights on the basis that it has shown competitive performance on continuous optimisation problems, is self-adaptive and can exploit dependencies between connection weights. Practical implementation issues are identified and discussed. A series of experiments are conducted on RL problems. These problems are representative of problems from the AUV domain, but manageable in terms of problem complexity and computational resources required. Results from these experiments are analysed to draw out practical characteristics of neuroevolution. Bulk experiments are conducted using the inverted pendulum problem. This popular control benchmark is inherently unstable, underactuated and non-linear: characteristics common to underwater vehicles. Two practical characteristics of neuroevolution are demonstrated: the importance of using randomly generated evaluation sets and the effect of evaluation noise on search performance. As part of these experiments, deficiencies in the benchmark are identified and modifications suggested. The problem of an underwater vehicle travelling to a goal in an obstacle free environment is studied. The vehicle is modelled as a Dubins car, which is a simplified model of the high-level kinematics of a torpedo class underwater vehicle. Two practical characteristics of neuroevolution are demonstrated: the importance of domain knowledge when formulating ANN inputs and how the fitness function defines the set of evolvable control policies. Paths generated by the evolved neurocontrollers are compared with known optimal solutions. A framework is presented to guide the practical application of neuroevolution to RL problems that covers a range of issues identified during the experiments conducted in this thesis. An assessment of neuroevolution concludes that it is far from automatic yet still has potential as a technique for solving reinforcement problems, although further research is required to better understand the process of evolutionary learning. The major contribution made by this thesis is a rigorous empirical study of the practical characteristics of neuroevolution as applied to RL problems. A critical, yet constructive, viewpoint is taken of neuroevolution. This viewpoint differs from much of the reseach undertaken in this field, which is often unjustifiably optimistic and tends to gloss over difficult practical issues.

O ambiente aquático tem notória importância para a pesquisa, pela biodiversidade e vastidão, e também do ponto de vista comercial, para a indústria militar e de óleo&gás por exemplo. Entretanto, a sua exploração é prejudicada por diversos fatores, entre eles devido à dificuldade de navegação. Infelizmente, carece-se de sinal GPS (Global Positioning System) embaixo d\'água, o que exige outras técnicas de localização. Assim, este trabalho analisa um sistema de navegação para um veículo submarino autônomo. Graças a sensores de velocidade, girômetros, bússola, entre outros, aplica-se o princípio de dead reckoning para calcular a posição atual do veículo a partir da última posição conhecida. Para tal, é feito inicialmente um estudo dos sensores a serem utilizados e um algoritmo de navegação é proposto, cujos resultados são expressos em coordenadas geodésicas (latitude e longitude), permitindo a visualização da trajetória do veículo em mapas geo-referenciados. Além disso, problemas práticos de medição são tratados. Em seguida, é feito um estudo sobre o ruído dos sensores, utilizando a curva de variância de Allan para caracterização dos sinais dos girômetros e do DVL (Doppler Velocity Logger). Por meio de equações de propagação de erro, os ruídos são recuperados em simulação, permitindo a estimação do erro de posição e de atitude (posição angular) acumulados para uma dada manobra. Finalmente, discute-se um critério de emersão a partir das estimativas de erro de posição. / The main part of our planet is filled with water, so the aquatic environment has notorious research and commercial importance. However, its exploration faces many difficulties. In navigation, the lack of GPS signal (Global Positioning System) during underwater missions requires different techniques, so this document focus on analyzing a navigation system for autonomous underwater vehicles. Thanks to different embedded sensors, like DVL (Doppler Velocity Logger), compass, gyrometers and others, the processes of dead reckoning is applied, witch calculates vehicle\'s current position by using the previously determined position. To do so, a navigation algorithm is implemented, providing geodesic coordinates to plot vehicle\'s trajectories on geo-referenced maps. Also, practical difficulties are discussed and treated. To improve the quality of the results, girometer\'s and DVL\'s errors are analyzed using Allan\'s variance and the navigation errors are estimated using first order time derivative equations in an augmented state space. Lastly, it is discussed a criterion to emerge and correct the vehicle\'s position using GPS signal.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: Sonars are used extensively for underwater sensing and recent advances in forward-looking imaging sonar have made this type of sonar an appropriate choice for use on Autonomous Underwater Vehicles. The images received from these sonar do however, tend to be noisy and when used in shallow water contain strong bottom reflections that obscure returns from actual targets. The focus of this work was the investigation and development of post-processing techniques to enable the successful use of the sonar images for automated navigation. The use of standard image processing techniques for noise reduction and background estimation, were evaluated on sonar images with varying amounts of noise, as well as on a set of images taken from an AUV in a harbour. The use of multiple background removal and noise reduction techniques on a single image was also investigated. To this end a performance measure was developed, based on the dynamic range found in the image and the uniformity of returned targets. This provided a means to quantitatively compare sets of post-processing techniques and identify the “optimal” processing. The resultant images showed great improvement in the visibility of target areas and the proposed techniques can significantly improve the chances of correct target extraction. / AFRIKAANSE OPSOMMING: Sonars word algemeen gebruik as onderwater sensors. Onlangse ontwikkelings in vooruit-kykende sonars, maak hierdie tipe sonar ’n goeie keuse vir die gebruik op ’n Outomatiese Onderwater Voertuig. Die beelde wat ontvang word vanaf hierdie sonar neig om egter raserig te wees, en wanneer dit in vlak water gebruik word toon dit sterk bodemrefleksies, wat die weerkaatsings van regte teikens verduister. Die fokus van die werk was die ondersoek en ontwikkeling van naverwerkings tegnieke, wat die sonar beelde bruikbaar maak vir outomatiese navigasie. Die gebruik van standaard beeldverwerkingstegnieke vir ruis-onderdrukking en agtergrond beraming, is geëvalueer aan die hand van sonar beelde met verskillende hoeveelhede ruis, asook aan die hand van ’n stel beelde wat in ’n hawe geneem is. Verdere ondersoek is ingestel na die gebruik van meer as een agtergrond beramings en ruis onderdrukking tegniek op ’n enkele beeld. Hierdie het gelei tot die ontwikkeling van ’n maatstaf vir werkverrigting van toegepaste tegnieke. Hierdie maatstaf gee ’n kwantitatiewe waardering van die verbetering op die oorspronklike beeld, en is gebaseer op die verbetering in dinamiese bereik in die beeld en die uniformiteit van die teiken se weerkaatsing. Hierdie maatstaf is gebruik vir die vergelyking van verskeie tegnieke, en identifisering van die “optimale” verwerking. Die verwerkte beelde het ’n groot verbetering getoon in die sigbaarheid van teikens, en die voorgestelde tegnieke kan ’n betekenisvolle bedrae lewer tot die suksesvolle identifisering van obstruksies.

Approved for public release, distribution is unlimited / 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. / Ensign, United States Navy / Captain, United States Air Force