"Micro aerial vehicles (MAV) are small remotely piloted or autonomous aircraft. Wingspans of MAVs can be as small as six inches to allow MAV’s to avoid detection during reconnaissance missions. Improving the aerodynamic efficiency of MAV’s by increasing the lift to drag ratio could lead to increased MAV range and endurance or future decreases in aircraft size. In this project, biologically inspired flight is used as a framework to improve MAV performance since MAV’s operate in a similar flight regime to birds. A novel wind tunnel apparatus was constructed that allows the planform shape of a MAV wing to be easily altered. The scale-model wing mimics a bird wing by using variable feather lengths to vary the wing planform shape. Genetic algorithms that use natural selection as an optimization process were applied to establish successive populations of candidate wing shapes. These wing shapes were tested in the wind tunnel where wings with higher fitness values were allowed to ‘breed’ and create a next generation of wings. After numerous generations were tested an acceptably strong solution was found that yielded a lift to drag ratio of 3.28. This planform was a non conventional planform that further emphasized the ability of a genetic algorithm to find a novel solution to a complex problem. Performance of the best planform was compared to previously published data for conventional MAV planform shapes. Results of this comparison show that while the highest lift to drag ratio found from the genetic algorithm is lower than published data, inabilities of the test wing to accurately represent a flat plate Zimmerman planform and limitations of the test setup can account for these discrepancies."

Remote sensing helps many applications like precision irrigation, habitat mapping, and traffic monitoring. However, due to shortcomings of current remote sensing platforms - like high cost, low spatial, and temporal resolution - many applications do not have access to useful remote sensing data. A team at the Center for Self-Organizing and Intelligent Systems (CSOIS) together with the Utah Water Research Laboratory (UWRL) at Utah State University has been developing a new remote sensing platform to deal with these shortcomings in order to give more applications access to remote sensing data. This platform (AggieAir) is low cost, fully autonomous, easy to use, independent of a runway, has a fast turnover time, and a high spatial resolution. A program called the Geospatial Real-Time Aerial Image Display (gRAID) has also been developed to process the images taken from AggieAir. gRAID is able to correct the camera lens distortion, georeference, and display the images on a 3D globe, and export them in a conventional Geographic Information System (GIS) format for further processing. AggieAir and gRAID prove to be innovative and useful tools for remote sensing.

Despite the explosion of popularity of UASs, and the recognition that such systems must find a way to safely operate alongside manned aviation, a literature review by this author as well as interviews with three commercial aerial photography companies in Tampa Bay, Florida, indicate that regulatory restrictions are still the greatest obstacle to law abiding commercial UAS operators. It can take six to eight months with a backlog of 12,000 waiver applications to get either a Part 333 or Part 107 exemption, which grants FAA permission for a commercial operator to fly a UAS inside controlled airspace (Gardner, 2018). A manned pilot can file a flight plan and hover a helicopter over the same area in just a few hours. The purpose of this research was to determine what industry experts perceive the future of UAS regulations hold, and how the industry will be impacted in both the short term of 5 years and less, and long-term of 5 years or more. UAS industry expert interviews were conducted in the “reflection of the meaning”, semi-structured style, with each interviewee given the latitude to discuss topics as they came to mind. A preset approved bank of questions helped to guide the interview, but in many cases as experts in the field, the interviewees naturally discussed the topics covered in the preset questions and the interview adapted to avoid unnecessary repetition. One interview was conducted in-person, but the rest were via phone calls due to geographical separation.

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies.Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data.Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes.Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The accuracy achieved in the second and third manuscripts demonstrates that reasonably priced, high resolution remote sensing via RPVs and UAVs is practical for agriculture and natural resource professionals.

Thesis--School of Advanced Airpower Studies, 1995. / Shipping list no.: 1998-0921-M. "February 1998." Includes bibliographical references. Also available via Internet from the Air University Press web site. Address as of 11/7/03: http://aupress.au.af.mil/SAAS%5FTheses/Treadway/treadway.pdf; current access is available via PURL.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 113-119).

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 274-285).

Thesis (M.S.)--Humboldt State University, 2006. / Includes bibliographical references (leaves 43-46). Also available via Humboldt Digital Scholar.

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A system was developed to perform real-time biological threat agent (BTA) detection with a small autonomous unmanned aerial vehicle (UAV). Biological sensors just recently reached a level of miniaturization and sensitivity that made UAV integration a feasible task. A Surface Plasmon Resonance (SPR) biosensor was integrated for the first time into a small UAV platform, allowing the UAV platform to collect and then quantify the concentration of an aerosolized biological agent in real-time. A sensor operator ran the SPR unit through a groundstation laptop and was able to wirelessly view detection results in real time. An aerial sampling mechanism was also developed for use with the SPR sensor. The collection system utilized a custom impinger setup to collect and concentrate aerosolized particles. The particles were then relocated and pressurized for use with the SPR sensor. The sampling system was tested by flying the UAV through a ground based plume of water soluble dye. During a second flight test utilizing the onboard SPR sensor, a sucrose solution was autonomously aerosolized, collected, and then detected by the combined sampling and SPR sensor subsystems, validating the system\'s functionality. The real-time BTA detection system has paved the way for future work quantifying biological agents in the atmosphere and performing source localization procedures. / Master of Science