How does a view from the ground reshape the analytics of US drone warfare? Through an ethnographic exploration of drone warfare from one of its sites of destruction—Pakistan and its borderlands known as the Tribal Areas—this dissertation troubles the notion of war-at-a-distance. Far from being at a remove, the war for many Pakistanis is in their neighborhoods, their fields, and their homes. Especially for ethnic Pashtuns who live amidst the drone war in the borderlands, attack drones are one element among a violent network—from Pakistani military helicopters to ground operations to armed guerrilla movements—that create radical disruptions. It is this dialectic between U.S. attacks and Pakistani state machinations that both produces ‘drone warfare’ and informs the analytics of Pashtuns and Pakistanis more generally vis-à-vis drone bombardment. By interrogating the relationship between drone attacks and the pluriverse of differentially distributed violence in the border zone, this dissertation traces the multi-scalar entanglements of the US imperial formation and the Pakistani state through which drone warfare and the ‘war on terror’ take shape in the Tribal Areas. Through an ethnographically situated account of the material, embodied geographies and conditions of the war zone, I show how these entanglements shape the geopolitics of the Pakistani state and position ethnic Pashtuns as multiply inflected: tribal-ized marginals, ethnic-ized citizens, and racialized transnational-ized targets of the ‘war on terror.’ In so doing, Grounding Drone Warfare shows that the remoteness of drone warfare is less an empirical reality than an authorizing self-narration of an imperial formation that prefers to frame itself as temporary and limited.

The military's desire for ducted fan vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) stems from the vehicles' relatively small size, safety in tight quarters, increased payload capacity for their size, and their ability to hover for surveillance missions. However, undesirable aerodynamic characteristics are associated with these vehicles in crosswinds, namely momentum drag and asymmetric duct lift. Because the duct itself, and not the fan, is the root cause of these unfavorable aerodynamic attributes, various lip shapes were tested to determine the effects of leading edge radius of curvature and duct wall thickness. It was found that a lip with a small leading edge radius performed best in forward flight and crosswind conditions, while the performance of a lip with a large leading edge radius was enhanced in static conditions. Through tuft flow visualization and static pressure measurements it was determined that the reason for the difference in performance between the two lips was due to flow separation on the interior of the duct lip surface. Control vanes positioned aft of the duct were tested as the primary attitude control for the vehicle. An empirical control vane model was created based on the static data for the control vanes, and it was applied to wind tunnel test results to determine the required control vane angle for trim. Wind tunnel testing showed the control vanes were capable of trimming out the adverse pitching moment generated by the duct, but at some flight speeds large vane deflections were necessary. Additional control devices placed at the lip of the duct and stabilizer vanes positioned aft of the duct were tested to reduce the amount of control vane deflection required for trim. It was found that the duct deflector control effector had the largest impact on the adverse pitching moment, while the stabilizer vanes were only effective at low crosswind velocities. / Master of Science

Differences in the aerodynamic performance data obtained at different test facilities were observed for the Wortmann FX-63-l37 airfoil. Earlier investigations found that the size of the hysteresis loop was affected by the tunnel environment and that single strut mounting of a three dimensional wing model interfered negligibly with the wing. Theoretical and experimental evaluations of a half wing model mounted with an end plate gap were done. Vortex panel method was used in the theoretical evaluation. The results from this indicated an effect of reduced aspect ratio with increase in end plate gap size. Tests were conducted in the VPI Stability Tunnel at low Reynolds numbers for different gap sizes including sealed gap. Results from the experiments showed that even very small gaps produce substantial changes in zero lift angle of attack (αu) and the change in αu, was reduced as Reynolds number increased. Sealed gap test results did not show such a behavior. Flow visualization of the flow through the gap showed a significant flow through the gap even at very low Reynolds number and small gap size. / Master of Science

This thesis proposes the design of the UAV-LMDS communication system for military and commercial use. The UAV-LMDS system is a digital, wireless communication system that provides service using unmanned aerial vehicles (UAVs) flying at 60,000 ft. acting as communication hubs. This thesis provides background information on UAV-LMDS system elements, a financial analysis, theory, link budgets, system component design and implementation issues. To begin the design, we develop link budgets that are used to characterize system parameters. We present detailed antenna designs for the antennas aboard the UAV. We also present communication equipment block diagrams. Included are technical details on military and commercial geostationary satellites used to link transmissions in the system. Implementation issues in the military system are discussed. Mobility and the effects of vegetation in the propagation path are investigated and a co-channel interference study is done. This thesis shows that by using UAVs and LMDS, a viable, broadband, wireless communications system can be created for military and commercial use. / Master of Science

A system is described for identifying obstacle-free landing sites for a vertical-takeoff-and-landing (VTOL) semi-autonomous unmanned aerial vehicle (UAV) from point cloud data obtained from a stereo vision system. The relatively inexpensive, commercially available Bumblebee stereo vision camera was selected for this study. A "point cloud viewer" computer program was written to analyze point cloud data obtained from 2D images transmitted from the UAV to a remote ground station. The program divides the point cloud data into segments, identifies the best-fit plane through the data for each segment, and performs an independent analysis on each segment to assess the feasibility of landing in that area. The program also rapidly presents the stereo vision information and analysis to the remote mission supervisor who can make quick, reliable decisions about where to safely land the UAV. The features of the program and the methods used to identify suitable landing sites are presented in this thesis. Also presented are the results of a user study that compares the abilities of humans and computer-supported point cloud analysis in certain aspects of landing site assessment. The study demonstrates that the computer-supported evaluation of potential landing sites provides an immense benefit to the UAV supervisor. / Master of Science

In recent years, significant progress has been made in improving the performance of unmanned air vehicles in terms of aerodynamic performance, endurance, autonomy, and the capability of on-board sensor packages. UAVs are now a vital part of both military actions and scientific research efforts. One of the newest classes of UAV is the high altitude long endurance or HALE UAV. This thesis considers the high-level control problem for a unique HALE mission involving cooperative solar powered UAVs. Specifically addressed is energy efficient path planning for vehicles that physically link together in flight to form a larger, more energy efficient HALE vehicle. Energy efficient docking is developed for the case of multiple vehicles at high altitude with negligible wind. The analysis considers a vehicle governed by a kinematic motion model with bounded turn rate in planar constant altitude flight. Docking is demonstrated using a platform-in-the-loop simulator which was developed to allow virtual networked vehicles to perform decentralized path planning and estimation of all vehicle states. Vehicle behavior is governed by a status which is commanded by a master computer and communication between vehicles is intermittent depending on each vehicle's assessment of situational awareness. Docking results in a larger vehicle that consumes energy at 21% of the rate of an individual vehicle and increases vehicle range by a factor of three without considering solar recharging. / Master of Science

The rapid, accurate determination of the positions and strengths of sources of dangerous radioactivity takes high priority after a catastrophic event to ensure the safety of personnel, civilians, and emergency responders. This thesis presents approaches and algorithms to autonomously investigate radioactive material using an unmanned aerial vehicle. Performing this autonomous analysis comprises five major steps: ingress from a base of operations to the danger zone, initial detection of radioactive material, measurement of the strength of radioactive emissions, analysis of the data to provide position and intensity estimates, and finally egress from the area of interest back to the launch site. In all five steps, time is of critical importance: faster responses promise potentially saved lives. A time-optimal ingress and egress path planning method solves the first and last steps. Vehicle capabilities and instrument sensitivity inform the development of an efficient search path within the area of interest. Two algorithms—a grid-based recursive Bayesian estimator and a novel radiation contour analysis method—are presented to estimate the position of radioactive sources using simple gross gamma ray event count data from a nondirectional radiation detector. The latter procedure also correctly estimates the number of sources present and their intensities. Ultimately, a complete unsupervised mission is developed, requiring minimal initial operator interaction, that provides accurate characterization of the radiation environment of an area of interest as quickly as reasonably possible. / Master of Science

This paper presents a new approach to the feature-matching problem for 3D reconstruction by taking advantage of GPS and IMU data, along with a prior calibrated stereo camera system. It is expected that pose estimates and calibration can be used to increase feature matching speed and accuracy. Given pose estimates of cameras and extracted features from images, the algorithm first enumerates feature matches based on stereo projection constraints in 2D and then backprojects them to 3D. Then, a grid search algorithm over potential camera poses is proposed to match the 3D features and find the largest group of 3D feature matches between pairs of stereo frames. This approach will provide pose accuracy to within the space that each grid region covers. Further refinement of relative camera poses is performed with an iteratively re-weighted least squares (IRLS) method in order to reject outliers in the 3D matches. The algorithm is shown to be capable of running in real-time correctly, where the majority of processing time is taken by feature extraction and description. The method is shown to outperform standard open source software for reconstruction from imagery. / Master of Science

The popularity and demand for safe autonomous vehicles are on the rise. Advances in semiconductor technology have led to the integration of a wide range of sensors with high-performance computers, all onboard the autonomous vehicles. The complexity of the software controlling the vehicles has also seen steady growth in recent years. Verifying the control software using traditional verification techniques is difficult and thus increases their safety concerns. Runtime verification is an efficient technique to ensure the autonomous vehicle's actions are limited to a set of acceptable behaviors that are deemed safe. The acceptable behaviors are formally described in linear temporal logic (LTL) specifications. The sensor data is actively monitored to verify its adherence to the LTL specifications using monitors. Corrective action is taken if a violation of a specification is found. An unmanned aerial vehicle (UAV) development platform is proposed for the validation of monitors on configurable hardware. A high-fidelity simulator is used to emulate the UAV and the virtual environment, thereby eliminating the need for a real UAV. The platform interfaces the emulated UAV with monitors implemented on configurable hardware and autopilot software running on a flight controller. The proposed platform allows the implementation of monitors in an isolated and scalable manner. Scenarios violating the LTL specifications can be generated in the simulator to validate the functioning of the monitors. / Master of Science / Safety is one of the most crucial factors considered when designing an autonomous vehicle. Modern vehicles that use a machine learning-based control algorithm can have unpredictable behavior in real-world scenarios that were not anticipated while training the algorithm. Verifying the underlying software code with all possible scenarios is a difficult task. Runtime verification is an efficient solution where a relatively simple set of monitors validate the decisions made by the sophisticated control software against a set of predefined rules. If the monitors detect an erroneous behavior, they initiate a predetermined corrective action. Unmanned aerial vehicles (UAVs), like drones, are a class of autonomous vehicles that use complex software to control their flight. This thesis proposes a platform that allows the development and validation of monitors for UAVs using configurable hardware. The UAV is emulated on a high-fidelity simulator, thereby eliminating the time-consuming process of flying and validating monitors on a real UAV. The platform supports the implementation of multiple monitors that can execute in parallel. Scenarios to violate rules and cause the monitors to trigger corrective actions can easily be generated on the simulator.

Autonomous robot missions in unknown environments are challenging. In many cases, the systems involved are unable to use a priori information about the scene (e.g. road maps). This is especially true in disaster response scenarios, where existing maps are now out of date. Areas without GPS are another concern, especially when the involved systems are tasked with navigating a path planned by a remote base station. Scene understanding via robots' perception data (e.g. images) can greatly assist in overcoming these challenges. This dissertation makes three contributions that help overcome these challenges, where there is a focus on the application of autonomously searching for radiation sources with unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) in unknown and unstructured environments. The three main contributions of this dissertation are: (1) An approach to overcome the challenges associated with simultaneously trying to understand 2D and 3D information about the environment. (2) Algorithms and experiments involving scene understanding for real-world autonomous search tasks. The experiments involve a UAV and a UGV searching for potentially hazardous sources of radiation is an unknown environment. (3) An approach to the registration of a UGV in areas without GPS using 2D image data and 3D data, where localization is performed in an overhead map generated from imagery captured in the air. / Ph. D. / Autonomous robot missions in unknown environments are challenging. In many cases, the systems involved are unable to use <i>a priori</i> information about the scene (<i>e.g.</i> road maps). This is especially true in disaster response scenarios, where existing maps are now out of date. Areas without GPS are another concern, especially when the involved systems are tasked with navigating a path planned by a remote base station. Scene understanding via robots’ perception data (<i>e.g.</i> images) can greatly assist in overcoming these challenges. This dissertation makes three contributions that help overcome these challenges, where there is a focus on the application of autonomously searching for radiation sources with unmanned aerial vehicles (UAV) and unmanned ground vehicles (UGV) in unknown and unstructured environments. The three main contributions of this dissertation are: (1) An approach to overcome the challenges associated with simultaneously trying to understand 2D and 3D information about the environment. (2) Algorithms and experiments involving scene understanding for real-world autonomous search tasks. The experiments involve a UAV and a UGV searching for potentially hazardous sources of radiation is an unknown environment. (3) An approach to the registration of a UGV in areas without GPS using 2D image data and 3D data, where localization is performed in an overhead map generated from imagery captured in the air.