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Unmanned Aerial Vehicle Research Facility
Unmanned Aerial Vehicle Research Facility
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ItemFeasibility Study to Determine the Economic and Operational Benefits of Utilizing Unmanned Aerial Vehicles (UAVs)(Georgia Institute of Technology, 2014-05-06) Irizarry, Javier ; Johnson, Eric N.This project explored the feasibility of using Unmanned Aerial Systems (UASs) in Georgia Department of Transportation (GDOT) operations. The research team conducted 24 interviews with personnel in four GDOT divisions. Interviews focused on (1) the basic goals of the operators in each division, (2) their major decisions for accomplishing those goals, and (3) the information requirements for each decision. Following an interview validation process, a set of UASs design characteristics that fulfill user requirements of each previously identified division was developed. A “House of Quality” viewgraph was chosen to capture the relationships between GDOT tasks and potential UAS aiding those operations. As a result, five reference systems are proposed. The UAS was broken into three components: vehicle, control station, and system. This study introduces a variety of UAS applications in traffic management, transportation and construction disciplines related to DOTs, such as the ability to get real time, digital photographs/videos of traffic scenes, providing a "bird’s eye view" that was previously only available with the assistance of a manned aircraft, integrating aerial data into GDOT drawing software programs, and dealing with restricted or complicated access issues when terrain, area, or the investigated object make it difficult for GDOT personnel to conduct a task. The results of this study could lead to further research on design, development, and field-testing of UAVs for applications identified as beneficial to the Department.
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ItemDevelopment and Evaluation of an Automated Path Planning Aid(Georgia Institute of Technology., 2012-11) Watts, Robert ; Christmann, Hans Claus ; Johnson, Eric N. ; Feigh, Karen M. ; Tsiotras, PanagiotisHandling en route emergencies in modern transport aircraft through adequate teamwork between the pilot, the crew and the aircraft’s automation systems is an ongoing and active field of research. An automated path planning aid tool can assist pilots with the tasks of selecting a convenient landing site and developing a safe path to land at this site in the event of an onboard emergency. This paper highlights the pilot evaluation results of a human factors study as part of such a proposed automated planning aid. Focusing on the interactions between the pilot and the automated planning aid, the presented results suggest that a particular implementation of the pilot aid interface, which uses a simple dial to sort the most promising landing sites, was effective. This selectable sorting capability, motivated by the anticipated cognitive mode of the pilot crew, improved the quality of the selected site for the majority of the cases tested. Although the presented approach increased the average time required for the selection of an alternate landing site, it decreased the time to complete the task in the case of emergencies unfamiliar to the pilot crew.
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ItemNetwork Discovery: An Estimation Based Approach(Georgia Institute of Technology, 2011-06) Chowdhary, Girish ; Egerstedt, Magnus B. ; Johnson, Eric N.We consider the unaddressed problem of network discovery, in which, an agent attempts to formulate an estimate of the global network topology using only locally available information. We show that under two key assumptions, the network discovery problem can be cast as a parameter estimation problem. Furthermore, we show that some form of excitation must be present in the network to be able to converge to a solution. The performance of two methods for solving the network discovery problem is evaluated in simulation.
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ItemMethodology to support dynamic function allocation polices between humans and flight deck automation(Georgia Institute of Technology, 2010-09-30) Johnson, Eric N.
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ItemModeling Urban Environments for Communication-Aware UAV Swarm Path Planning(Georgia Institute of Technology, 2010-08) Christmann, Hans Claus ; Johnson, Eric N.The presented work introduces a graph based approach to model urban (or otherwise cluttered) environments for UAS utilization beyond line-of-sight as well as out of direct R/F range of the operator's control station. Making the assumption that some a priori data of the environment is available, the proposed method uses a classification of obstacles with respect to their impact on UAV motion and R/F communication and generates continuously updateable graphs usable to compute traverseable paths for UAVs while maintaining R/F communication. Using a simulated urban scenario this work shows that the proposed modeling method allows to find reachable loiter or hover areas for UAVs in order to establish a multi-hop R/F communication link between a primary UAV and its remote operator by utilizing an overlay of motion (Voronoi based) and R/F (visibility based) specific mapping methods.
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ItemVisual Marker Detection In The Presence Of Colored Noise for Unmanned Aerial Vehicles(Georgia Institute of Technology, 2010-04) Shah, Syed Irtiza Ali ; Wu, Allen D. ; Johnson, Eric N.This paper develops a vision-based algorithm to detect a visual marker in real time and in the presence of excessive colored noise for Unmanned Aerial Vehicles. After using various image analysis techniques, including color histograms, filtering techniques and color space analyses, typical pixel-based characteristics of the visual marker were established. It was found that not only various color space based characteristics were significant, but also relationships between various channels across different color spaces were of great consequence. A block based search algorithm was then used to search for those established characteristics in real-time image data stream from a colored camera. A low cost noise and interference filter was also devised to handle excessive noise that was encountered during flight tests. The specific implementation scenario is that of detection of a Blue LED for GeorgiaTech's participating aircraft into the International Aerial Robotics competition. The final algorithm that was implemented on GTAR lama aircraft, used both multiple thresholding and linear confidence level calculations and was successfully used in the competition in 2009.