This paper looks to the natural world for solutions to many of the challenges associated with the design of fixed-wing cross-domain vehicles. One example is the common murre, a seabird that flies from nesting locations to feeding areas, dives underwater to catch prey and returns. This hunting expedition provides an outline of a possible mission for a cross-domain vehicle. While the challenges of cross-domain vehicles are many, the focus of this paper was on buoyancy management and propulsion. Potential solutions to each challenge, inspired by multiple animals that cross between aerial and underwater domains, are investigated. From these solutions, three design concepts are considered, a quadrotor/fixed-wing hybrid, a vertical takeoff and landing (VTOL) tailsitter aircraft, and a waterjet-assisted takeoff vehicle. A comparison was made between the capability of each concept to complete two missions based on the common murres' hunting expedition. As a result of this comparison, the VTOL tailsitter design was selected for further study. In-depth design was conducted and a prototype vehicle was built. The completed vehicle prototype successfully conducted submerged operation as well as four air flights. Flights consisted of egress from water, flight in air, ingress into water in each flight, and water locomotion. A total of 11 min, 23 s of flight time was recorded as well as underwater swims down to 12 ft (3.7 m) below the surface.

POWERS, THOMAS CORNELIUS. Artificial Lumbered Flight for Autonomous Soaring. (Under the direction of Drs. Larry Silverberg and Ashok Gopalarathnam).Soaring strategies are redefining the flight capabilities of small-class fixed-wing UAVs. This dissertation presents an autonomous soaring strategy that exploits updraft energy independent of the classification of an updraft. The strategy employs an artificial lumbered flight algorithm (ALFA) that weighs near-field updraft velocity estimates and mission priorities for navigation. This work raises the question of ALFA's ability to handle classified updrafts. Indeed, ALFA does not explicitly consider the classification of the updraft. Instead, ALFA measures updraft data along an aircraft's flight path, estimates updraft data ahead of the aircraft, generates candidate flightpaths ahead of the aircraft for evaluation, and then selects the best candidate flightpath based on a reward function. This dissertation describes the structure of ALFA and the tuning processes for the updraft estimator and the decision function.Flight results demonstrate the ability of artificial lumbered flight to harness atmospheric energy and complete its objectives. The flight results consider aircraft behavior in more detail, examining ALFA's effectiveness when flying among classified updrafts. They demonstrate the ability of artificial lumbered flight to navigate unclassified updrafts and harvest energy from thermal updrafts. Finally, this work highlights that autonomous flight design and control of small-class aircraft is maturing into its own flight regime that lies between the flapping flight and cruise flight regimes, and will be driven by the harvesting of energy from the atmosphere.

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