Organizational Unit:

Unmanned Aerial Vehicle Research Facility

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https://hdl.handle.net/1853/70748

Parent Organization

Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1139

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Publication Search Results

Now showing 1 - 10 of 54

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.
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.
Situational and Terrain Awareness and Warning System Implementation on Android Smartphone for Manned Aviation Applications

(Georgia Institute of Technology, 2014-01) Bershadsky, Dmitry ; Dressel, Louis ; Johnson, Eric N.

General aviation (GA) aircraft are for the most part not equipped with situational awareness or alerting systems, namely in terms of traffic or terrain collision. This is largely due to lack of regulatory requirements, but also because such systems tend to be costly. By over an order of magnitude, these types of aircraft are the most common in the world's airspace. Their prevalence, combined with their more terrain-proximal flight profiles, make GA aircraft most susceptible to controlled flight into terrain (CFIT) incidents. We introduce an economical situational awareness and alerting system in an attempt to mitigate CFIT accidents in otherwise uninstrumented GA aircraft. We do so using a common smartphone to run an application which interfaces with NASA's Shuttle Radar Topography Mission (SRTM) digital terrain elevation database (DTED).
Speed Profile Optimization for Optimal Path Tracking

(Georgia Institute of Technology, 2013-11) Zhao, Yiming ; Tsiotras, Panagiotis

In this paper, we study the problem of minimum-time, and minimum-energy speed profile optimization along a given path, which is a key step for solving the optimal path tracking problems for a particular class of dynamical systems. We focus on characterizing the optimal switching structure between extremal controls using optimal control theory, and present semi-analytical solutions to both problems. It is shown that the optimal solutions of these two problems are closely related.
Georgia Tech Team Entry for the 2013 AUVSI International Aerial Robotics Competition

(Georgia Institute of Technology, 2013-08) Magree, Daniel ; Bershadsky, Dmitry ; Costes, Chris ; Haviland, Stephen ; Sanz, David ; Kim, Eric ; Valdez, Pierre ; Dyer, Timothy ; Johnson, Eric N.
Improving Uniform Ultimate Bounded Response of Neuroadaptive Control Approaches Using Command Governors

(Georgia Institute of Technology, 2013-08) Magree, Daniel ; Yucelen, Tansel ; Johnson, Eric N.

In this paper, we develop a command governor-based architecture in order to improve the response of neuroadaptive control approaches. Specifically, a command governor is a linear dynamical system that modifies a given desired command to improve transient and steady-state performance of uncertain dynamical systems. It is shown that as the command governor gain is increased, the neuroadaptive system converges to the linear reference system. Simulation results are used to validate the effectiveness of the proposed framework.
Indoor GPS-denied Context Based SLAM Aided Guidance for Autonomous Unmanned Aerial Systems

(Georgia Institute of Technology, 2013-08) Bershadsky, Dmitry ; Johnson, Eric N.

Autonomous exploration and mapping of environments is an important problem in robotics. Efficient exploration of structured environments requires that the robot utilize region-specific exploration strategies and coordinate with search other agents. This paper details the exploration and guidance system of a multi-quadrotor unmanned aerial system (UAS) capable of exploring cluttered indoor areas without relying on any external aides. Specifically, a graph-based frontier search algorithm which is aided by an onboard Simultaneous Localization and Mapping (SLAM) system is developed and flight tested. A technique is developed in for segmenting an indoor office-like environment into regions and to utilize the SLAM map to conduct specific activities in these regions. A goal-directed exploration strategy is created building on existing hybrid deliberative-reactive approaches to exploration. An obstacle avoidance and guidance system is implemented to ensure that the vehicle explores maximum indoor area while avoiding obstacles. The environment is explored and regions are segmented by detecting rooms and hallways which expedites the search. The multi-vehicle system is Georgia Tech Aerial Robotic Team's entry for the annual International Aerial Robotics Competition (IARC).