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Micro aerial vehicle development and atmospheric flight on Mars are areas that require research in very low Reynolds number flight. Facilities for studying these problems are not widely available. The upper atmosphere of the Earth, approximately 100,000 feet AGL, is readily available and closely resembles the atmosphere on Mars, in both temperature and density. This low density also allows normal size test geometry with a very low Reynolds number. This solves a problem in micro aerial vehicle development; it can be very difficult to manufacture instrumented test apparatus in the small sizes required for conventional testing. This thesis documents the design, construction, and testing of a glider designed to be released from a weather balloon at 100,000 feet AGL and operate in this environment, collecting airfoil and aircraft performance data. The challenges of designing a vehicle to operate in a low Reynolds number, low temperature environment are addressed.

Aircraft modeling and simulation have become increasingly important in the areas of pilot training, safety and aircraft design, especially for unmanned aerial vehicles (UAVs). A userriendly, easily expandable, nonlinear six degree-ofreedom aircraft simulator for the Xipiter X-2C Xawk UAV was created to address these issues. The simulator will allow pilots to have an opportunity to train and gain experience in flying the aircraft even before it leaves the ground. In addition, it will allow for design modifications or new aircraft designs to be evaluated before time and money are spent on their implementation. This work can also serve as the basis for the development of control systems for the aircraft, such as a control augmentation system or autopilot.

Micro Aerial Vehicles (MAVs) provide a highly capable, agile platform, ideally suited for intelligence/surveillance/reconnaissance missions, urban search and rescue, and scientific exploration. Critical to the success of these tasks is a system which moves au-tonomously through an unknown, obstacle-strewn, GPS-denied environment. Classical simultaneous localization and mapping (SLAM) approaches rely on large, heavy sensors to generate 3-D information about a MAV’s surroundings, severely limiting its abilities. This motivates a study of Parallel Tracking and Mapping (PTAM), an algorithm requiring only a single camera to provide 3-D data to an autonomous navigation system. Metric properties of 3-D MAV pose estimates are compared with physical measurements to ex-plore tracking accuracy. Additionally, a discrete wavelet transform-based keypoint detec-tor is implemented for a feasibility study on improving map density in low-visual-detail environments. Finally, a system is presented that integrates PTAM, autonomous MAV control, and a human interface for manual control and data logging.

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In recent years, dramatic evolution of precision agriculture technology has been driven by technologies such as sensors and controllers, telematics, and UAV. An intriguing area in the field of precision agriculture and UAV is big volume of data and its analysis that have not been dealt with in depth. The main objective of this project is proposed to develop a digital data processing tool and deliver them in a useful format to the end users. This involves three faceted methodical approach: 1) collection of large amounts of UAV images with regards to combinations of in-field sensors and UAV imagery 2) analyze and validate the combination of data with geospatial tools 3) Develop a web-based computer data processing program to analyze the big data and assess pant condition. The validation and correlation analysis results showed that UAV assessed NDVI are good indicator of crop nutrition along with the ground-based crop sensors.