Organizational Unit:

Unmanned Aerial Vehicle Research Facility

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

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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 13

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.
Development 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, Panagiotis

Handling 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.
Self-Contained Autonomous Indoor Flight with Ranging Sensor Navigation

(Georgia Institute of Technology, 2012-11) Chowdhary, Girish ; Sobers, D. Michael, Jr. ; Pravitra, Chintasid ; Christmann, Hans Claus ; Wu, Allen ; Hashimoto, Hiroyuki ; Ong, Chester ; Kalghatgi, Roshan ; Johnson, Eric N.

This paper describes the design and flight test of a completely self-contained autonomous indoor Miniature Unmanned Aerial System (M-UAS). Guidance, navigation, and control algorithms are presented, enabling the M-UAS to autonomously explore cluttered indoor areas without relying on any off-board computation or external navigation aids such as GPS. The system uses a scanning laser rangefinder and a streamlined Simultaneous Localization and Mapping (SLAM) algorithm to provide a position and heading estimate, which is combined with other sensor data to form a six degree-of-freedom inertial navigation solution. This enables an accurate estimate of the vehicle attitude, relative position, and velocity. The state information, with a self-generated map, is used to implement a frontier-based exhaustive search of an indoor environment. Improvements to existing guidance algorithms balance exploration with the need to remain within sensor range of indoor structures such that the SLAM algorithm has sufficient information to form a reliable position estimate. A dilution of precision metric is developed to quantify the effect of environment geometry on the SLAM pose covariance, which is then used to update the 2-D position and heading in the navigation filter. Simulation and flight test results validate the presented algorithms.
Integrated Guidance Navigation and Control for a Fully Autonomous Indoor UAS

(Georgia Institute of Technology, 2011-08) Chowdhary, Girish ; Sobers, D. Michael, Jr. ; Pravitra, Chintasid ; Christmann, Hans Claus ; Wu, Allen ; Hashimoto, Hiroyuki ; Ong, Chester ; Kalghatgi, Roshan ; Johnson, Eric N.

This paper describes the details of a Quadrotor miniature unmanned aerial system capable of autonomously exploring cluttered indoor areas without relying on any external navigational aids such as GPS. A streamlined Simultaneous Localization and Mapping (SLAM) algorithm is implemented onboard the vehicle to fuse information from a scanning laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. This state information, with a self-generated map, is used to implement a frontier-based exhaustive search of an indoor environment. To ensure the SLAM algorithm has sufficient information to form a reliable solution, the guidance algorithm ensures the vehicle approaches frontier waypoints through a path that remains within sensor range of indoor structures. Along with a detailed description of the system, simulation and hardware testing results are presented.
A Simulation Engine to Predict Multi-Agent Work in Complex, Dynamic, Heterogeneous Systems

(Georgia Institute of Technology, 2011-02) Pritchett, Amy R. ; Christmann, Hans Claus ; Bigelow, Matthew S.

This paper documents a simulation engine developed to accurately and efficiently simulate work by multiple agents in complex dynamic systems. Agents (human or mechanical) are modeled as responding to, and changing, their environment by executing the actions that get and set the value of resources in the environment. Each action comprises the processes that need to be evaluated at the same time by the same agent, which are used to reference (get) resources, consider them according to simple or complicated processes, and then interact back on the environment by setting resources appropriately. This paper specifically addresses timing within the simulation. The simplest approach would update all actions at the smallest unit of conceivable time, an approach that is not only computationally inefficient, but also not an accurate representation of situated behavior. Instead, every action declares its next update time as required to accurately model its internal dynamics and the simulation engine executes them asynchronously. Thus, an action and the resources it ’gets’ from the environment are not inherently contemporary; instead, each action also specifies, for each resource value that it gets, the quality of service required in terms of its temporal currency. This reflects dynamics of the real processes being simulated: when, in actual operations, would the environment be sampled, and how accurately must its state be known? Additionally, this also reflects dynamics of environmental resources how often (or how fast) does each inherently change? Using these constructs, the list of actions to be simulated are sorted by the simulation engine according to their next update time. Each action, when its time comes, is given to their agent model to be executed, and then is sorted back into the action list according to its self-reported next update time. Thus, actions are each updated when they need to be. In situations where, for example, action Y needs to get a resource which, because action X has not set it recently, does not meet action Ys required Quality of Service. The simulation engine will invoke action X immediately before action Y, mimicking cases in the real system where one process calls on another to establish the conditions it needs. The presented simulation engine is a complete redevelopment, designed and written from scratch at the Cognitive Engineering Center at the Georgia Institute of Technology.
Visibility Cues for Communication Aware Guidance in Cluttered Environments

(Georgia Institute of Technology, 2011) Christmann, Hans Claus ; Johnson, Eric N.

This paper presents the usage of visibility based guidance cues in order to find waypoints useful for maintaining communication in a multi UAV (Uninhabited Aerial Vehicle), single operator system. Based upon the overlay of visibility graphs (for radio communication) and Voronoi diagrams (for maximum clearance motion paths), the paper presents simulations of three staged methods, allowing the computation of waypoints suitable for establishing a potential multi-hop connection between an operator and a primary UAV in an urban or otherwise cluttered environment. The methods present generic solutions for 2D planes, ensuring applicability for indoor, outdoor, and other structured environments through a potential interconnection of several non-coplanar 2D planes. The presented methods increase in computational complexity as they are capable of handling more complex scenarios. However, the presented methods are overall still deemed computationally acceptable and present themselves as good candidates for onboard implementation on vehicles with limited computational power.
Modeling 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.
A Language for Describing Agent Behavior as Hybrid Models

(Georgia Institute of Technology, 2009-08) Kannan, Suresh K. ; Christmann, Hans Claus ; Lee, Seungman ; Johnson, Eric N. ; Kim, So Y. K

Air Traffic conflict detection and resolution (CDR) involves multiple domains, the modeling of physical systems such as aircraft, encoding conflict detection algorithms as well as the procedures(tasks) for conflict resolution. Depending on the analysis being conducted, an implementation language is usually chosen to cater for easy rendering of algorithms in the primary domain of interest. The more specialized the choice of implementation language, the greater the difficulty in expanding the fidelity of models in other domains. This paper takes a unified view of continuous equations, algorithms and procedures. Events that occur in sequence as well as in parallel are represented in a unified manner by interpreting them as hierarchical state-charts at a low-level and as procedures or task trees at a higher level. The relationship between the two levels are recognized and utilized in decomposing task trees in to hierarchical state charts and eventually into C++ code for implementation.
An ILS Inspired Approach and Departure System Utilizing Monocular Vision

(Georgia Institute of Technology, 2009-07) Christmann, Hans Claus ; Johnson, Eric N.

This paper introduces a simple system to provide relative position between a base unit and an active unit. The proposed system is directional and allows the active unit to approach or depart from the base unit along a linear path, determined by the orientation of the base unit. The system does not require a data link between the base and the active unit, just a clear line of sight. The proposed system utilizes monocular vision on the active unit and requires the availability of enough computational power to perform simple computer vision algorithms. Part I describes the physical characteristics of the beacon utilized on the base unit, Part II describes the algorithms utilized to compute the relative position of the active unit to the base, utilizing the vision data. Part III presents simulation results. Part IV discusses the results and findings and proposes future work.
Georgia Tech Aerial Robotics Team: 2009 International Aerial Robotics Competition Entry

(Georgia Institute of Technology, 2009-07) Chowdhary, Girish ; Christmann, Hans Claus ; Johnson, Eric N. ; Salaün, Erwan ; Sobers, D. Michael Jr.

This paper examines the use of low-cost range and target identification sensors on a stable flying vehicle for suitability in solving the 5th Mission proposed for the 2009 International Aerial Robotics Competition. The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics. Using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments reduces the complexity of the localization and mapping problem to the point that wall and obstacle location can be determined using low-cost range sensors. Target identification is accomplished remotely using an onboard video camera with a radio transmitter. Thus complex and time-consuming image processing routines are run on a more powerful computer, enabling further miniaturization of the flight vehicle.