Augmented Terrain-Based Navigation to Enable Persistent Autonomy for Underwater Vehicles in GPS-Denied Environments

Aquatic robots, such as Autonomous Underwater Vehicles (AUVs), play a major role in the study of ocean processes that require long-term sampling efforts and commonly perform navigation via dead-reckoning using an accelerometer, a magnetometer, a compass, an IMU and a depth sensor for feedback. However, these instruments are subjected to large drift, leading to unbounded uncertainty in location. Moreover, the spatio-temporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in coastal regions where the majority of interesting phenomena occur. To add to this, the interesting features are themselves spatio-temporally dynamic, and effective sampling requires a good understanding of vehicle localization relative to the sampled feature. Therefore, our work is motivated by the desire to enable intelligent data collection of complex dynamics and processes that occur in coastal ocean environments to further our understanding and prediction capabilities. The study originated from the need to localize and navigate aquatic robots in a GPS-denied environment and examine the role of the spatio-temporal dynamics of the ocean into the localization and navigation processes. The methods and techniques needed range from the data collection to the localization and navigation algorithms used on-board of the aquatic vehicles. The focus of this work is to develop algorithms for localization and navigation of AUVs in GPS-denied environments. We developed an Augmented terrain-based framework that incorporates physical science data, i.e., temperature, salinity, pH, etc., to enhance the topographic map that the vehicle uses to navigate. In this navigation scheme, the bathymetric data are combined with the physical science data to enrich the uniqueness of the underlying terrain map and increase the accuracy of underwater localization. Another technique developed in this work addresses the problem of tracking an underwater vehicle when the GPS signal suddenly becomes unavailable. The methods include the whitening of the data to reveal the true statistical distance between datapoints and also incorporates physical science data to enhance the topographic map. Simulations were performed at Lake Nighthorse, Colorado, USA, between April 25th and May 2nd 2018 and at Big Fisherman\u27s Cove, Santa Catalina Island, California, USA, on July 13th and July 14th 2016. Different missions were executed on different environments (snow, rain and the presence of plumes). Results showed that these two methodologies for localization and tracking work for reference maps that had been recorded within a week and the accuracy on the average error in localization can be compared to the errors found when using GPS if the time in which the observations were taken are the same period of the day (morning, afternoon or night). The whitening of the data had positive results when compared to localizing without whitening

In-situ characterization of sea state with improved navigation on an Autonomous Underwater Glider

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2022.This thesis presents an Autonomous Underwater Glider (AUG) architecture with improved onboard navigation and acoustics-based sensing intended to enable basin-scale unattended surveys of our Earth’s most remote oceans. Traditional AUGs have long-been an important platform for oceanographic surveys due to their high endurance and autonomy, yet lack the operational flexibility to operate in many regions of scientific interest and the sensing capability to capture scientific data at the air-sea interface. Particularly of interest is the marginal ice zone (MIZ) in the Arctic and the Southern Ocean, as both are vitally important to understanding global climate trends, yet prohibitively expensive to persistently monitor with support vessels. To fill this observational gap, the sensing, navigation, and adaptability of AUGs must be improved. This is possible by employing onboard acoustic sensing for sea state observation and navigation, as well as incorporating vehicle improvements targeting maneuverability and intelligent adaptability to evolving environmental states. To enable persistent monitoring of both the water-column and air-sea interface, this thesis proposes an improved vehicle architecture for a more capable AUG, a real-time DVLaided navigation process that leverages ocean current sensing to limit localization error, and a subsea acoustics-based sea state characterization method capable of analyzing wave spectra under-ice and with zero surface expression. These methods are evaluated with respect to extensive laboratory experiments and field data collected during in-situ implementation.Support for this research was provided through grants from the National Science Foundation (NSF) Navigating the New Arctic Grant (NNA #1839063) and the National Ocean Partnership Program (NOPP) Enhanced Propulsion Integrated Capability - Deep Autonomous Underwater Glider (EPIC-DAUG) grant (NA19OAR0110408)

Satellites to the Seafloor: Autonomous Science to Forge a Breakthrough in Quantifying the Global Ocean Carbon Budget

Understanding the global carbon budget and its changes is crucial to current and future life on Earth. The marine component represents the largest reservoir of the global carbon cycle. In addition to physical processes that govern carbon fluxes at the air-sea interface and regulate the atmospheric carbon budget, complex internal sources and sinks, including inorganic, geologic, microbiological and biological processes also impact carbon distributions and storage. Therefore, it is essential to observe and understand the whole system. This is a daunting task, as many of the processes are distributed throughout the ocean, laterally and vertically over scales ranging from centimeters to thousands of kilometers. Ship and satellite observations both offer a partial view but, for ships, are either too short term and localized and satellites, despite their large spatial coverage, lack the spatial resolution. Ocean robots, such as deep diving autonomous underwater vehicles (AUVs) and gliders, provide in-situ observations of the seafloor and water column while the surface can be observed in-situ by autonomous surface vehicles (ASVs). Presently, these assets are used disparately with each operating independently and requiring direct human intervention for data interpretation and mission retasking. This paradigm is insufficient for the task of obtaining the millions of in-situ and remote measurements necessary for quantifying the ocean’s contribution to the global carbon cycle. This study brings together scientists, who understand the imperative and scope of quantifying the global carbon budget, with technologists, who may be able to glimpse a possible way of solving it. A coordinated network of ocean robots and satellites that autonomously interpret data and communicate sampling strategies could significantly advance our ability to monitor the marine carbon (and other biogeochemical) cycles. The principal goal of this study is to determine whether emerging technologies could enable crucial oceanographic and space science investigations to be coordinated to address this scientific challenge and may be the way to address others. Specifically, we will: establish a lingua franca between the participants’ different research communities that will enable increased communication; identify the observational capabilities required to quantify the carbon cycle; assess the present capabilities of the ocean robotics, autonomous science, and satellite communities to provide these capabilities; investigate if coordinated ocean robots and satellites using autonomous science can obtain those observations; and develop a collaborative research agenda aimed at solving these problems

Towards basin-scale in-situ characterization of sea-ice using an Autonomous Underwater Glider

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2020.This thesis presents an Autonomous Underwater Glider (AUG) architecture that is intended for basin-scale unattended survey of Arctic sea-ice. The distinguishing challenge for AUG operations in the Arctic environment is the presence of year-round sea-ice cover which prevents vehicle surfacing for localization updates and shore-side communication. Due to the high cost of operating support vessels in the Arctic, the proposed AUG architecture minimizes external infrastructure requirements to brief and infrequent satellite updates on the order of once per day. This is possible by employing onboard acoustic sensing for sea-ice observation and navigation, along with intelligent management of onboard resources. To enable unattended survey of Arctic sea-ice with an AUG, this thesis proposes a hierarchical acoustics-based sea-ice characterization scheme to perform science data collection and assess environment risk, a multi-factor terrain-aided navigation method that leverages bathymetric features and active ocean current sensing to limit localization error, and a set of energy-optimal propulsive and hotel policies that react to evolving environmental conditions to improve AUG endurance. These methods are evaluated with respect to laboratory experiments and preliminary field data, and future Arctic sea-ice survey mission concepts are discussed.Support for this research was provided through the National Science Foundation Navigating the New Arctic Grant #1839063 and the NASA PSTAR Grant #NNX16AL08G. Additionally, this research was supported by the Walter A. Rosenblith Presidential Fellowship

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Unmanned Vehicle Systems & Operations on Air, Sea, Land

Unmanned Vehicle Systems & Operations On Air, Sea, Land is our fourth textbook in a series covering the world of Unmanned Aircraft Systems (UAS) and Counter Unmanned Aircraft Systems (CUAS). (Nichols R. K., 2018) (Nichols R. K., et al., 2019) (Nichols R. , et al., 2020)The authors have expanded their purview beyond UAS / CUAS systems. Our title shows our concern for growth and unique cyber security unmanned vehicle technology and operations for unmanned vehicles in all theaters: Air, Sea and Land – especially maritime cybersecurity and China proliferation issues. Topics include: Information Advances, Remote ID, and Extreme Persistence ISR; Unmanned Aerial Vehicles & How They Can Augment Mesonet Weather Tower Data Collection; Tour de Drones for the Discerning Palate; Underwater Autonomous Navigation & other UUV Advances; Autonomous Maritime Asymmetric Systems; UUV Integrated Autonomous Missions & Drone Management; Principles of Naval Architecture Applied to UUV’s; Unmanned Logistics Operating Safely and Efficiently Across Multiple Domains; Chinese Advances in Stealth UAV Penetration Path Planning in Combat Environment; UAS, the Fourth Amendment and Privacy; UV & Disinformation / Misinformation Channels; Chinese UAS Proliferation along New Silk Road Sea / Land Routes; Automaton, AI, Law, Ethics, Crossing the Machine – Human Barrier and Maritime Cybersecurity.Unmanned Vehicle Systems are an integral part of the US national critical infrastructure The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. Unmanned Vehicle (UV) Systems & Operations On Air, Sea, Land discusses state-of-the-art technology / issues facing U.S. UV system researchers / designers / manufacturers / testers. We trust our newest look at Unmanned Vehicles in Air, Sea, and Land will enrich our students and readers understanding of the purview of this wonderful technology we call UV.https://newprairiepress.org/ebooks/1035/thumbnail.jp

Boundary tracking and source seeking of oceanic features using autonomous vehicles

The thesis concerns the study and the development of boundary tracking and source seeking approaches for autonomous vehicles, specifically for marine autonomous systems. The underlying idea is that the characterization of most environmental features can be posed from either a boundary tracking or a source seeking perspective. The suboptimal sliding mode boundary tracking approach is considered and, as a first contribution, it is extended to the study of three dimensional features. The approach is aimed at controlling the movement of an underwater glider tracking a three-dimensional underwater feature and it is validated in a simulated environment. Subsequently, a source seeking approach based on sliding mode extremum seeking ideas is proposed. This approach is developed for the application to a single surface autonomous vehicle, seeking the source of a static or dynamic two dimensional spatial field. A sufficient condition which guarantees the finite time convergence to a neighbourhood of the source is introduced. Furthermore, a probabilistic learning boundary tracking approach is proposed, aimed at exploiting the available preliminary information relating to the spatial phenomenon of interest in the control strategy. As an additional contribution, the sliding mode boundary tracking approach is experimentally validated in a set of sea-trials with the deployment of a surface autonomous vehicle. Finally, an embedded system implementing the proposed boundary tracking strategy is developed for future installation on board of the autonomous vehicle. This work demonstrates the possibility to perform boundary tracking with a fully autonomous vehicle and to operate marine autonomous systems without remote control or pre-planning. Conclusions are drawn from the results of the research presented in this thesis and directions for future work are identified

The Sleeping Giant: Measuring Ocean-Ice Interactions in Antarctica

Global sea level rise threatens to be one of the most costly consequences of human-caused climate change. And yet, projections of sea level rise remain poorly understood and highly uncertain. The largest potential contribution to global sea level rise involves the loss of ice covering all or even a portion of Antarctica. As global atmospheric and ocean temperatures rise, physical processes related to the ocean’s circulation: (i) carry this additional heat into the deep ocean, (ii) transport it poleward via the overturning circulation and (iii) ultimately deliver the heat to the underside of floating Antarctic ice shelves. Enhanced melting that occurs due to warm ocean waters plays an important role in the loss of ice from the continent. Our understanding of the first two steps that bring heat towards Antarctica has increased substantially over the past two decades through improved measurements of air-sea interactions and interior ocean properties (e.g., Argo). Yet, the constraints on the oceanic delivery of heat to Antarctic ice shelves and its impact on melt rates remains critically under-studied. Our inability to constrain the rate of retreat of Antarctic glaciers and how the Antarctic Ice Sheet will behave in a warming climate remains the single most significant reason for the large uncertainty in sea level projections over the 21st century. This problem is the focus of the KISS study, "The Sleeping Giant: Measuring Ocean Ice Interactions in Antarctica," and stands as one of the grand challenges of climate science today

A Virtual Ocean framework for environmentally adaptive, embedded acoustic navigation on autonomous underwater vehicles

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2021.Autonomous underwater vehicles (AUVs) are an increasingly capable robotic platform, with embedded acoustic sensing to facilitate navigation, communication, and collaboration. The global positioning system (GPS), ubiquitous for air- and terrestrial-based drones, cannot position a submerged AUV. Current methods for acoustic underwater navigation employ a deterministic sound speed to convert recorded travel time into range. In acoustically complex propagation environments, however, accurate navigation is predicated on how the sound speed structure affects propagation. The Arctic’s Beaufort Gyre provides an excellent case study for this relationship via the Beaufort Lens, a recently observed influx of warm Pacific water that forms a widespread yet variable sound speed lens throughout the gyre. At short ranges, the lens intensifies multipath propagation and creates a dramatic shadow zone, deteriorating acoustic communication and navigation performance. The Arctic also poses the additional operational challenge of an ice-covered, GPSdenied environment. This dissertation demonstrates a framework for a physics-based, model-aided, real-time conversion of recorded travel time into range—the first of its kind—which was essential to the successful AUV deployment and recovery in the Beaufort Sea, in March 2020. There are three nominal steps. First, we investigate the spatio-temporal variability of the Beaufort Lens. Second, we design a human-in-the-loop graphical decision-making framework to encode desired sound speed profile information into a lightweight, digital acoustic message for onboard navigation and communication. Lastly, we embed a stochastic, ray-based prediction of the group velocity as a function of extrapolated source and receiver locations. This framework is further validated by transmissions among GPS-aided modem buoys and improved upon to rival GPS accuracy and surpass GPS precision. The Arctic is one of the most sensitive regions to climate change, and as warmer surface temperatures and shrinking sea ice extent continue to deviate from historical conditions, the region will become more accessible and navigable. Underwater robotic platforms to monitor these environmental changes, along with the inevitable rise in human traffic related to trade, fishing, tourism, and military activity, are paramount to coupling national security with international climate security.Office of Naval Research (N00014-14-1-0214) — GOATS’14 Adaptive and Collaborative Exploitation of 3-Dimensional Environmental Acoustics in Distributed Undersea Networks Draper Laboratory Incorporated (SC001-0000001039) — Positioning System for Deep Ocean Navigation (POSYDON) Office of Naval Research (N00014-16-1-2129) — MURI: The Information Content of Ocean Noise: Theory and Experiment Office of Naval Research (N00014-17-1-2474) — Environmentally Adaptive Acoustic Communication and Navigation in the New Arctic Office of Naval Research (N00014-19-1-2716) — TFO: Assessing Realism and Uncertainties in Navy Decision Aids Department of Defense, Office of Naval Research — National Defense, Science, and Engineering Graduate Fellowshi