Person:

Johnson, Eric N.

Permanent Link

https://hdl.handle.net/1853/72197

Associated Organization(s)

Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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Publication Search Results

Now showing 1 - 10 of 33

Single-operator Multi-vehicle Human-Automation Interface Study dataset

(Georgia Institute of Technology, 2015-05) Feigh, Karen M. ; Johnson, Eric N. ; Christmann, Hans Claus

With 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.
Development of a 500 gram Vision-based Autonomous Quadrotor Vehicle Capable of Indoor Navigation

(Georgia Institute of Technology, 2015-05) Haviland, Stephen ; Bershadsky, Dmitry ; Magree, Daniel ; Johnson, Eric N.

This paper presents the work and related research done in preparation for the American Helicopter Society (AHS) Micro Aerial Vehicle (MAV) Student Challenge. The described MAV operates without human interaction in search of a ground target in an open indoor environment. The Georgia Tech Quadrotor-Mini (GTQ-Mini) weighs under 500 grams and was specifically sized to carry a high processing computer. The system platform also consists of a monocular camera, sonar, and an inertial measurement unit (IMU). All processing is done onboard the vehicle using a lightweight powerful computer. A vision navigation system generates vehicle state data and image feature estimates in a vision SLAM formation using a Bierman Thornton extended Kalman Filter (BTEKF). Simulation and flight tests have been performed to show and validate the systems performance.
A Monocular Vision-aided Inertial Navigation System with Improved Numerical Stability

(Georgia Institute of Technology, 2015-01) Magree, Daniel ; Johnson, Eric N.

This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop.
Longitudinal Motion Planning for Slung-Loads Using Simplified Models and Rapidly-Exploring Random Trees

(Georgia Institute of Technology, 2015-01) Johnson, Eric N. ; Mooney, John G.

A randomized motion-planning approach to providing guidance for helicopters with under-slung loads is presented. Rapidly-exploring Random Trees are adapted to plan trajectories for simplified helicopter-load models. Four different planning models are tested against four different representative tasks. The poor performance of the baseline planner, and subsequent efforts to improve that performance shows the sensitivity of the RRT to proper sizing of the sampling area and amount of computation available. Further lines of potential research into optimizing planner performance and reducing computational cost are identified.
Feasibility 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.
A 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.
Benchmarking of UAV Guidance Systems in Nap of the Earth (NOE) Flight

(Georgia Institute of Technology, 2014-05) Johnson, Eric N. ; Bershadsky, Dmitry

This paper describes the development of a proposed framework of metrics for the evaluation of the performance of aircraft guidance systems. The methodologies and metrics developed remain generally agnostic to whether or not the aircraft is manned. Although more complicated missions such as autonomous exploration/search, ferry, surveillance, multi-agent collaboration, and manned flight may be addressed at a later time, A-B flight scenarios are chosen to study the proposed metrics. The proposed metrics will form building blocks for the more complicated missions. Metrics development has thus far generally focused on NOE flight, and in particular on the observability of the vehicle throughout its mission. That is, a formulation of probability of detection by potential and generally unknown threats in the mission area will be the main metric. Secondary metrics provide insight into the vehicle's trajectory quality in terms of safety and comfort, experienced by both humans and machines are described as well. Scalability of the benchmarking system is also important and benchmarking should be general enough to allow guidance algorithms to be graded independently of the vehicle platform, for instance. Non-dimensionalization metrics will address this concern.
Collaborative 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.
A Comprehensive Matrix of Unmanned Aerial Systems Requirements for Potential Applications within a Department of Transportation

(Georgia Institute of Technology, 2014) Karan, Ebrahim P. ; Christmann, Hans Claus ; Gheisar, Masoud ; Irizarry, Javier ; Johnson, Eric N.

The continuous improvement in the function and performance of Unmanned Aerial Systems (UASs) promotes the need for specific research to integrate this leading edge technology in to various applications across Departments of Transportation (DOTs). DOTs of several states have started looking into using UAS technology for different purposes from tracking highway construction projects and performing structure inventories to road maintenance, monitoring roadside environmental conditions, as well as many other traffic management or safety issues, albeit individually focusing on specific us age scenarios. This study investigates various divisions and offices within a Department of Transportation to determine the operational requirements for UAS usage in specific divisions which have the potential to implement this technology to aid and supplement their daily operations. Through a series of interviews with subject matter experts at the management and operational levels, a matrix of user requirements for tasks that have the potential to use UAS is developed. This matrix is mapped to a UAS technical matrix that embeds the technological and technical requirements for development of a potential UAS. These matrices can be used by other DOTs for defining the design specifications for UAS that can fulfill their construction related operational requirements.
Monocular Visual Mapping for Obstacle Avoidance on UAVs

(Georgia Institute of Technology, 2014-01) Magree, Daniel ; Mooney, John G. ; Johnson, Eric N.

An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict payload and power constraints which limit the number and variety of sensors available to gather this information. It is desirable, therefore, to enable a UAV to gather information about potential obstacles or interesting landmarks using common and lightweight sensor systems. This paper presents a method of fast terrain mapping with a monocular camera. Features are extracted from camera images and used to update a sequential extended Kalman filter. The features locations are parameterized in inverse depth to enable fast depth convergence. Converged features are added to a persistent terrain map which can be used for obstacle avoidance and additional vehicle guidance. Simulation results, results from recorded flight test data, and flight test results are presented to validate the algorithm.