Presented is a method for estimating the planar position, velocity, and orientation states of a tagged shark. The method is designed for implementation on an Autonomous Underwater Vehicle (AUV) equipped with a stereo-hydrophone and receiver system that detects acoustic signals transmitted by a tag. The particular hydrophone system used here provides a measurement of relative bearing angle to the tag, but does not provide the sign (+ or -) of the bearing angle. A particle filter was used for fusing measurements over time to produce a state estimate of the tag location. The particle filter combined with an active control system allowed the system to overcome the ambiguity in the sign of the bearing angle. This state estimator was validated by tracking a stationary tag and moving tag with known positions. These experiments revealed state estimate errors were on par with those obtained by manually driven boat based tracking systems, the current method used for tracking fish and sharks over long distances. Final experiments involved the catching, releasing, and an autonomous AUV tracking of a 1 meter leopard shark (Triakis semifasciata) in SeaPlane Lagoon, Los Angeles, California.

Autonomous underwater vehicles (AUVs) have the potential to dramatically improve safety, quality of life and general scientific knowledge. Our coasts, lakes and rivers are filled with various forms of marine infrastructure including dams, bridges, ship hulls, communication lines, and oil rigs. Each of these structures requires regular inspection, and current methods utilize divers, which is dangerous, expensive, and time consuming. AUVs have the potential to alleviate these difficulties and enable more regular inspection of these structures. Furthermore, there are significant scientific discoveries in the fields of geology, marine biology and medicine that AUV exploration of our oceans will enable. Since field trials of AUVs can be both expensive and high-risk, making a simulation method to generate data for algorithm development is a necessity. For this purpose, we present HoloOcean, an open-source, fully-featured, underwater robotics simulator. Built upon Unreal Engine 4 (UE4), HoloOcean comes equipped with multi-agent communications, common underwater sensors, high-fidelity graphics, and a novel sonar simulation method. Our novel sonar simulation framework is built upon an octree structure, allowing for rapid data generation and flexible usage to simulate a variety of sonars. Further, we have augmented this simulation to incorporate various probabilistic models to account for the heavy noise found in sonar imagery. Simulation enables development of many algorithms such as mapping, localization, structure from motion, controls, and many others. Localization is one essential algorithm for AUV navigation. Recent developments in the utilization of Lie Groups for robotic localization have lead to dramatic performance improvements in convergence and uncertainty characterization. One such method, the Invariant Extended Kalman Filter (InEKF), leverages that invariant error dynamics defined on matrix Lie Groups satisfy a log-linear differential equation. We lay out the various practical decisions required for the InEKF, and show that the primary sensors used in underwater robotics with minor modifications can be used in the InEKF. We show the convergence improvements of the InEKF over the quaternion-based extended Kalman filter (QEKF) on HoloOcean data, both in low and high uncertainty scenarios.

In nature, through millions of years of evolution, fish and cetaceans have developed fast efficient and highly manoeuvrable methods of marine propulsion. A recent explosion in demand for sub sea robotics, for conducting tasks such as sub sea exploration and survey has left developers desiring to capture some of the novel mechanisms evolved by fish and cetaceans to increase the efficiency of speed and manoeuvrability of sub sea robots. Research has revealed that interactions with vortices and other unsteady fluid effects play a significant role in the efficiency of fish and cetaceans. However attempts to duplicate this with robotic fish have been limited by the difficulty of predicting or sensing such uncertain fluid effects. This study aims to develop a gait generation method for a robotic fish with a degree of passivity which could allow the body to dynamically interact with and potentially synchronise with vortices within the flow without the need to actually sense them. In this study this is achieved through the development of a novel energy based gait generation tactic, where the gait of the robotic fish is determined through regulation of the state energy rather than absolute state position. Rather than treating fluid interactions as undesirable disturbances and `fighting' them to maintain a rigid geometric defined gait, energy based control allows the disturbances to the system generated by vortices in the surrounding flow to contribute to the energy of the system and hence the dynamic motion. Three different energy controllers are presented within this thesis, a deadbeat energy controller equivalent to an analytically optimised model predictive controller, a $H_\infty$ disturbance rejecting controller with a novel gradient decent optimisation and finally a error feedback controller with a novel alternative error metric. The controllers were tested on a robotic fish simulation platform developed within this project. The simulation platform consisted of the solution of a series of ordinary differential equations for solid body dynamics coupled with a finite element incompressible fluid dynamic simulation of the surrounding flow. results demonstrated the effectiveness of the energy based control approach and illustrate the importance of choice of controller in performance.

L'objectif de cette thèse, en collaboration avec une équipe de biologistes de Marbec, est de développer un système robotisé semi-autonome pour l’observation des espèces marines. Pour cela, ce système devra effectuer les protocoles biologistes connus ainsi que de nouveaux protocoles tout en démontrant son efficacité par rapport à un plongeur. Pour réaliser correctement les protocoles, nous avons développé les lois de commande associées ainsi qu'un système de gestion de mission pour permettre la construction, la validation formelle et l'exécution d'une telle mission. Enfin, pour répondre à la problématique de faisabilité de l'observation par un robot, nous avons mené les expérimentations à Mayotte. / The goal of this thesis, in collaboration with a biologists team of Marbec, is to develop a semi-autonomous robotic system for marine species observation. For this, this system will have to perform the known biologist protocols as well as new protocols while proving its effectiveness compared to a diver. To achieve the protocols, we have developed the associated control laws and a mission management system to allow the construction, the formal validation and the execution of a mission. Finally, to answer the problem of feasibility of observation by a robot, we conducted the experiments in Mayotte.

abstract: The need for incorporating game engines into robotics tools becomes increasingly crucial as their graphics continue to become more photorealistic. This thesis presents a simulation framework, referred to as OpenUAV, that addresses cloud simulation and photorealism challenges in academic and research goals. In this work, OpenUAV is used to create a simulation of an autonomous underwater vehicle (AUV) closely following a moving autonomous surface vehicle (ASV) in an underwater coral reef environment. It incorporates the Unity3D game engine and the robotics software Gazebo to take advantage of Unity3D's perception and Gazebo's physics simulation. The software is developed as a containerized solution that is deployable on cloud and on-premise systems. This method of utilizing Gazebo's physics and Unity3D perception is evaluated for a team of marine vehicles (an AUV and an ASV) in a coral reef environment. A coordinated navigation and localization module is presented that allows the AUV to follow the path of the ASV. A fiducial marker underneath the ASV facilitates pose estimation of the AUV, and the pose estimates are filtered using the known dynamical system model of both vehicles for better localization. This thesis also investigates different fiducial markers and their detection rates in this Unity3D underwater environment. The limitations and capabilities of this Unity3D perception and Gazebo physics approach are examined. / Dissertation/Thesis / Masters Thesis Computer Science 2020

This dissertation explores a novel omnidirectional propulsion mechanism for observation-class underwater vehicles, enabling for operation in extreme, hostile, or otherwise high-speed turbulent environments where unprecedented speed and agility are necessary. With a small overall profile, the mechanism consists of two sets of counter-rotating blades operating at frequencies high enough to dampen vibrational effects on onboard sensors. Each rotor is individually powered to allow for roll control via relative motor effort and attached to a swashplate mechanism, providing quick and powerful manipulation of fluid-flow direction in the hull's coordinate frame without the need to track rotor position. The omnidirectional mechanism exploits properties emerging from its continuous counter-rotating blades to generate near-instantaneous forces and moments in six degrees of freedom (DOF) of considerable magnitude, and is designed to allow each DOF to be controlled independently by one of six decoupled control parameters. The work presented in this dissertation validates the mechanism through physical small-scale experimentation, confirming near-instantaneous reaction time, and aligning with computational fluid dynamic (CFD) results presented for the proposed theorized full-scale implementation. Specifically, it is demonstrated that the mechanism can generate sway thrust at 10-20% surge thrust capacity in both simulation and physical tests. It is also shown that the magnitude of forces and moments generated is directly proportional to motor effort and corresponding commands, in par with theory. Any apparent couplings between different control modes are deeply understood and shown to be trivially accounted for, effectively uncoupling all six control parameters. The design, principles, and bullard-pull simulation of the proposed full-scale mechanism and vehicle implementation are then thoroughly discussed. Kinematic and hydrodynamic analyses of the hull and surrounding fluid forces during different maneuvers are presented, followed by the mechanical design and kinematic analysis of each subsystem. To estimate proposed full-scale performance specifications and UUV turbulence rejection, a full six-DOF maneuvering model is constructed from first principles utilizing CFD and regression techniques. This dissertation thoroughly examines the working principles and performance of a novel omnidirectional propulsion mechanism. With the small-scale model and full scale simulation and analysis, the work presented successfully demonstrates the mechanism can generate nearly instantaneous omnidirectional forces underwater in a controlled manner, with application to high-speed agile vehicles in dynamic environments. / Doctor of Philosophy / This dissertation explores a novel omnidirectional propulsion mechanism for observation-class underwater vehicles, enabling for operation in extreme, hostile, or otherwise high-speed turbulent environments where unprecedented speed and agility are necessary. The mechanism utilizes independently-powered rotors to command near-instantaneous forces and moments in all six degrees of freedom (DOF). The design allows each DOF to be independently controlled by one of six decoupled control parameters. The method for generating lateral thrust through the mechanism is originally verified through computational fluid dynamic (CFD) tests, but the complete novelty of the lateral maneuver calls for physical verification for any noteworthy validation. The work presented in this dissertation validates the mechanism through physical small-scale experimentation, confirming near-instantaneous reaction time, and aligning with CFD results presented for the proposed theorized full-scale implementation. Specifically, it is demonstrated that the mechanism can generate sway (side/side) thrust at 10-20% surge (forward/backward) thrust capacity in both simulation and physical tests. It is also shown that the magnitude of forces and moments generated is directly proportional to motor effort and corresponding commands, in par with theory. Finally, a full six-DOF model for underwater vehicle trajectory is constructed utilizing detailed maneuvering techniques to estimate full-scale performance. With the small-scale model and full-scale simulation and analysis, the work successfully demonstrates the mechanism can generate nearly instantaneous omnidirectional forces underwater in a controlled manner, with application to high-speed agile vehicles in dynamic environments.

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.

<div>Exploring and surveilling the marine environment away from shore is critical for scientific, economic, and military purposes as we progress through the 21st century. Until recently, these missions far from shore were only possible using manned surface vehicles. Over the past decade, advances in energy density, actuators, electronics, and controls have enabled great improvements in vehicle endurance, yet, no solution is capable of supporting persistent operation especially when considering power hungry scientific surveys. This dissertation summarizes contributions related to the development of an adaptable underwater docking station and associated navigation solutions to allow applications in the wide range of maritime missions. The adaptable docking system is a novel approach to the standard funnel shaped docking station design that enables the dock to be collapsible, portable, and support a wide range of vehicles. It has been optimized and tested extensively in simulation. Field experiments in both pool and open water validate the simulation results. The associated control strategies for approach and terminal homing are also introduced and studied in simulation and field trials. These strategies are computationally efficient and enable operation in a variety of scenarios and conditions. Combined, the adaptable docking system and associated navigation strategies can form a baseline for future extended endurance missions away from manned support.</div>

<p dir="ltr">The technological advancements in marine robotics led to the expansion of the autonomous underwater vehicle (AUV) fleet. Depending on the applications, the type of the AUV ranges across various shapes and sizes. It seeks a solution for the issue of limited power capacity, often in terms of underwater docking systems. Underwater docking poses a significant challenge for AUVs, especially when considering the diverse shapes and sizes of these vehicles. Existing solutions usually are task specific, and do not address the idea of scalable underwater docking system design.<br>This thesis investigates the adaptability of the specific docking system design, previously validated for torpedo-shaped AUVs, to boxed-shaped AUVs in a nonlinear open water environment. In order to achieve this goal, the scalability of the docking system design of choice was tested in an open water non-linear underwater environment and validated. The scalability of the robust docking system was adapted to the box-shaped AUV, encompassing path planning, path following, and docking maneuver. The adapted docking system was based on the optic methods for docking station detection and subsequent docking. Additionally, the simulated environment was developed for the AUV model, for testing and debugging purposes. In the simulation, a custom PID controller was developed along with integrating the navigation and guidance package, to fully simulate the real life behavior of the AUV. </p><p dir="ltr">Furthermore, this work introduces a recurrent neural network-based architecture for investigating temporal dependencies of the sequential data input. The proposed architecture is based on CNN for spatial feature extraction and LSTM/GRU for temporal feature detection. The dataset collection is based on the simulation environment, by enhancing the artificial images with imposed realism. The dataset was gathered on different levels of turbidity and the collection process was automated.</p>

<p dir="ltr">Unmanned surface vehicles (USVs) offer a versatile platform for various maritime applications, including research, surveillance, and search-and-rescue operations. A critical capability for USVs is maintaining position (station keeping) in dynamic environments and coordinating movement with other USVs (formation control) for collaborative missions. This thesis investigates control strategies for USVs operating in challenging conditions. </p><p dir="ltr">The initial focus is on evaluating traditional control methods like Backstepping and Sliding Mode controllers for station keeping in simulated environments with disturbances. The results from these tests pointed towards the need for a more robust control technique, like deep-learning based control for enhanced performance. </p><p dir="ltr">The thesis then explores formation control, a crucial aspect of cooperative USV missions. A vision-based passive control strategy utilizing a virtual leader concept is proposed. This approach leverages onboard cameras to detect markers on other USVs, eliminating the need for direct communication and potentially improving scalability and resilience. </p><p dir="ltr">Then the thesis presents vision-based formation control architecture and the station keeping controller evaluations. Simulation results are presented, analyzed, and used to draw conclusions about the effectiveness of the proposed approaches. Finally, the thesis discusses the implications of the findings and proposes potential future research directions</p>