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Daniel Guggenheim School of Aerospace Engineering
Daniel Guggenheim School of Aerospace Engineering
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ItemState Estimation using Gaussian Process Regression for Colored Noise Systems(Georgia Institute of Technology, 2017-06) Lee, Kyuman ; Johnson, Eric N.The goal of this study is to use Gaussian process (GP) regression models to estimate the state of colored noise systems. The derivation of a Kalman filter assumes that the process noise and measurement noise are uncorrelated and both white. In relaxing those assumptions, the Kalman filter equations were modified to deal with the non-whiteness of each noise source. The standard Kalman filter ran on an augmented system that had white noises and other approaches were also introduced depending on the forms of the noises. Those existing methods can only work when the characteristics of the colored noise are perfectly known. However, it is usually difficult to model a noise without additional knowledge of the noise statistics. When the parameters of colored noise models are totally unknown and the functions of each underlying model (nonlinear dynamic and measurement functions) are uncertain or partially known, filtering using GP-Color models can perform regardless of whatever forms of colored noise. The GPs can learn the residual outputs between the GP models and the approximate parametric models (or between actual sensor readings and predicted measurement readings), as a member of a distribution over functions, typically with a mean and covariance function. Lastly, a series of simulations, including Monte Carlo results, will be run to compare the GP based filtering techniques with the existing methods to handle the sequentially correlated noise.
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ItemSingle-operator Multi-vehicle Human-Automation Interface Study dataset(Georgia Institute of Technology, 2015-05) Feigh, Karen M. ; Johnson, Eric N. ; Christmann, Hans ClausWith the achievement of autonomous flight for small unmanned aircraft, currently ongoing research is expanding the capabilities of systems utilizing such vehicles for various tasks. This allows shifting the research focus from the individual systems to task execution benefits resulting from interaction and collaboration of several aircraft. Given that some available high-fidelity simulations do not yet support multi-vehicle scenarios, a multi-vehicle framework has been introduced which allows several individual single-vehicle systems to be combined into a larger multi-vehicle scenario with little to no special requirements towards the single-vehicle systems. The created multi-vehicle system offers real-time software-in-the-loop simulations of vehicle teams across multiple hosts and enables a single operator to command and control a several unmanned aircraft beyond line-of-sight in geometrically correct two-dimensional cluttered environments through a multi-hop network of data relaying intermediaries. The related dissertation by Christmann presents the main aspects of the developed system: the underlying software framework and application programming interface, the utilized inter- and intrasystem communication architecture, the graphical user interface, and implemented algorithms and operator aid heuristics to support the management and placement of the vehicles.The effectiveness of the aid heuristics is validated through a human subject study which showed that the provided operator support systems significantly improve the operators' performance in a simulated first responder scenario. This dataset contains the collected data of that human subject study.
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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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ItemA Comparison of Automatic Nap-of-the-Earth Guidance Strategies for Helicopters(Georgia Institute of Technology, 2014-05) Johnson, Eric N. ; Mooney, John G.This paper describes updated results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance Nap-of-the-Earth (NOE) helicopter flight.
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ItemCollaborative Search and Pursuit for Autonomous Helicopters(Georgia Institute of Technology, 2014-05) Johnson, Eric N. ; Mooney, John G.This paper describes recent results to develop, improve, and flight test a multi-aircraft collaborative architecture, focused on decentralized autonomous decision-making. The architecture includes a search coverage algorithm, behavior estimation, and a pursuit algorithm designed to solve a scenario-driven challenge problem. The architecture was implemented on a pair of Yamaha RMAX helicopters outfitted with modular avionics, as well as an associated set of simulation tools. Simulation and flight test results for single- and multiple- aircraft scenarios are presented. Further work suggested includes identification and development of more sophisticated methods that can replace the simpler elements in modular fashion.
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ItemTerrain Height Evidence Sharing for Collaborative Autonomous Rotorcraft Operation(Georgia Institute of Technology, 2013-01) Johnson, Eric N. ; Mooney, John G. ; White, Matthew ; Hartman, Jonathan ; Sahasrabudhe, VineetThis paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time information sharing system to support collaborative autonomy and high performance nap-of-the-Earth helicopter flight. The emphasis here is on smart and selective sharing of terrain data which (1) minimizes the bandwidth consumed by obstacle/terrain-information-sharing between aircraft, (2) assigns an appropriate level of confidence to the data received from other heterogeneous aircraft, (3) is robust to sensor error and failures, and (4) is robust to entry and exit of vehicles from the network. Results from simulation and flight testing are provided.
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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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ItemAdvanced methods for intelligent flight guidance and planning in support of pilot decision making(Georgia Institute of Technology, 2012-03-01) Tsiotras, Panagiotis ; Johnson, Eric N.
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ItemFlight Testing of Nap of-the-Earth Unmanned Helicopter Systems(Georgia Institute of Technology, 2011-05) Johnson, Eric N. ; Mooney, John G. ; Ong, Chester ; Sahasrabudhe, Vineet ; Hartman, JonathanThis paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance nap-of-the-Earth helicopter flight. The emphasis here is on optimization for a combination of low height above terrain/obstacles and high speeds. Multiple methods for generating the desired flight path were evaluated, including (1) a simple processing of each laser scan; and (2) a potential field based method. Simulation and flight test results have been obtained utilizing an onboard laser scanner to detect terrain and obstacles while flying at low altitude, and have successfully demonstrated obstacle avoidance in a realistic semi-urban environment at speeds up to 40 ft/s while maintaining a miss distance of 50 ft horizontally and vertically. These results indicate that the technical approach is sound, paving the way for testing of even lower altitudes, higher speeds, and more aggressive maneuvering in future work.
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ItemHigh Performance Nap-of-the-Earth Unmanned Helicopter Flight(Georgia Institute of Technology, 2011) Johnson, Eric N. ; Mooney, John G. ; Ong, Chester ; Sahasrabudhe, Vineet ; Hartman, JonathanThis paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance nap-of-the-Earth helicopter flight. The emphasis here is on optimization for a combination of low height above terrain/obstacles and high speeds. Multiple methods for generating the desired flight path were evaluated, including (1) a simple processing of each laser scan; and (2) a potential field based method. Simulation and flight test results have been obtained utilizing an onboard laser scanner to detect terrain and obstacles while flying at low altitude, and have successfully demonstrated obstacle avoidance at speeds up to 40 ft/s while maintaining a miss distance of 50 ft horizontally and vertically. These results indicate that the technical approach is sound, paving the way for testing of even lower altitudes, higher speeds, and more aggressive maneuvering in future work.