WHOI Theses

Permanent URI for this collection

https://hdl.handle.net/1912/1172

WHOI's educational role, at the graduate level, was formalized in 1968 with a change in its charter and the signing of an agreement with the Massachusetts Institute of Technology for a Joint Program leading to doctoral (Ph.D. or Sc.D.) or engineer's degrees. Joint master's degrees are also offered in selected areas of the program. Woods Hole Oceanographic Institution is also authorized to grant doctoral degrees independently.

New theses are added as they are published.

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Browsing WHOI Theses by Author "Camilli, Richard"
  • Thesis
    Developing the next generation of Autonomous Underwater Gliders
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2022-09) Ventola, Peter T. ; Camilli, Richard
    This thesis presents a novel, hybrid Autonomous Underwater Glider (AUG) architecture developed for improved performance in shallow, high-current environments while maintaining all capabilities inherent to a deep, 1000m-rated AUG. Numerous regions of scientific interest, such as the marginal ice zone (MIZ) and continental shelf breaks present significant challenges to conventional AUG operations due to a combination of changing ocean currents and depths. AUGs are traditionally optimized for performance in shallow (less than 200m) or deep water (200m to 1000m) environments. The design of a buoyancy drive on a deep-rated AUG does not support the pump rate required for fast inflections in narrow depth bands. Contained within this thesis is the framework to expand the operational envelope of a Teledyne Webb Research (TWR) G3 Slocum glider through substantial modification of the glider’s hardware components backed by rigorous hydrodynamic analysis and computational fluid dynamics (CFD) modelling. Since AUGs are limited in both speed and maneuverability, the goal of this thesis is to improve and modify the glider’s flight characteristics, specifically the glider’s speed through water, its inflection rate, and its efficiency. These performance improvements are accomplished through the introduction of a high-power thruster, modified wings, and aft fin surfaces. The modified glider’s efficacy is evaluated through various laboratory experiments and field data obtained in Buzzards Bay and the Caribbean Sea. Design concepts for a future, more advanced glider are also discussed.
  • Thesis
    Enabling robotic manipulation in remote environments with shared autonomy
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2023-06) Phung, Amy ; Camilli, Richard ; Williams, Brian
    The evolution of robotics technology continues to facilitate exploration and scientific study in remote environments, enabling research in areas that were previously impossible to reach. Robots operating in space and marine environments encounter similar operational challenges, as both face high operational costs, bandwidth-limited conditions, and natural, unstructured environments where dynamic obstacles might be present. Within the oceanographic domain, conventional deep-sea sampling operations involve remotely operated vehicles (ROVs) equipped with robotic manipulator arms to complete dexterous tasks at depth. While effective, deep-sea ROV operations require specialized instrumentation, highly trained shipboard personnel, and large oceanographic vessels, which make deep-sea samples inaccessible to most. This thesis presents the SHared Autonomy for Remote Collaboration (SHARC) framework, and evaluates its utility within an oceanographic context. By leveraging shared autonomy, SHARC enables shore-side operators to collaboratively carry out underwater sampling and manipulation tasks, regardless of their prior manipulator operations experience. With SHARC, operators can conduct manipulation tasks using natural language and hand gestures through a virtual reality (VR) interface. The interface provides remote operators with a contextual 3D scene understanding that is updated according to bandwidth availability. Evaluation of the SHARC framework through controlled lab experiments indicates that SHARC’s VR interface enables novice operators to complete manipulation tasks in framerate-limited conditions (i.e., <0.5 frames per second) faster than expert pilots using the conventional topside controller. For both novice and expert users, the VR interface also increased the task completion rate and improved sampling precision. During sea trials, SHARC enabled collection of an underwater in-situ X-ray fluorescence (XRF) measurement at more than 1000 meters water depth in the Eastern Pacific with centimeter-level precision by remote scientists with no prior piloting experience. This demonstration provides compelling evidence of SHARC’s utility for conducting delicate operations in unstructured environments across bandwidthlimited communications, which holds relevance for improving operations in other sensitive domains where dexterity is required. SHARC’s ability to relax infrastructure requirements and engage novice shore-side users provides a promising avenue for democratizing access to deep-sea research.
  • Thesis
    Query-driven adaptive sampling
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2022-09) Ayton, Benjamin ; Williams, Brian C. ; Camilli, Richard
    Automated information gathering allows exploration of environments where data is limited and gathering observations introduces risk, such as underwater and planetary exploration. Typically, exploration has been performed in service of a query, with a unique algorithm developed for each mission. Yet this approach does not allow scientists to respond to novel questions as they are raised. In this thesis, we develop a single approach for a broad range of adaptive sampling missions with risk and limited prior knowledge. To achieve this, we present contributions in planning adaptive missions in service of queries, and modeling multi-attribute environments. First, we define a query language suitable for specifying diverse goals in adaptive sampling. The language fully encompasses objectives from previous adaptive sampling approaches, and significantly extends the possible range of objectives. We prove that queries expressible in this language are not biased in a way that avoids information. We then describe a Monte Carlo tree search approach to plan for all queries in our language, using sample based objective estimators embedded within tree search. This approach outperforms methods that maximize information about all variables in hydrocarbon seep search and fire escape scenarios. Next, we show how to plan when the policy must bound risk as a function of reward. By solving approximating problems, we guarantee risk bounds on policies with large numbers of actions and continuous observations, ensuring that risks are only taken when justified by reward. Exploration is limited by the quality of the environment model, so we introduce Gaussian process models with directed acyclic structure to improve model accuracy under limited data. The addition of interpretable structure allows qualitative expert knowledge of the environment to be encoded through structure and parameter constraints. Since expert knowledge may be incomplete, we introduce efficient structure learning over structural models using A* search with bounding conflicts. By placing bounds on likelihood of substructures, we limit the number of structures that are trained, significantly accelerating search. Experiments modeling geographic data show that our model produces more accurate predictions than existing Gaussian process methods, and using bounds allows structure to be learned in 50% of the time.
  • Thesis
    Towards basin-scale in-situ characterization of sea-ice using an Autonomous Underwater Glider
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2020-09) Duguid, Zachary ; Camilli, Richard
    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.