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 19

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.
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.
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).
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).