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 105

Modelling and Hardware-in-the-Loop Simulation for a Small Unmanned Aerial Vehicle

(Georgia Institute of Technology, 2007-05) Jung, Dongwon ; Tsiotras, Panagiotis ; Georgia Institute of Technology. School of Aerospace Engineering

Modeling and experimental identification results for a small unmanned aerial vehicle (UAV) are presented. The numerical values of the aerodynamic derivatives are computed via the Digital DATCOM software using the geometric parameters of the airplane. Flight test data are utilized to identify the stability and control derivatives of the UAV. The aerodynamic angles are estimated and used in conjunction with inertial measurements in a batch parameter identification algorithm. A hardware-in-the-loop (HIL) simulation environment is developed to support and validate the UAV autopilot hardware and software development. The HIL simulation incorporates a high-fidelity dynamic model that includes the sensor and actuator models, from the identified parameters from experiments. A user-friendly graphical interface that incorporates external stick commands and 3-D visualization of the vehicle’s motion completes the simulation environment. The hardware-in-the-loop setup is an indispensable tool for rapid certification of both the avionics hardware and the control software, while performing simulated flight tests with minimal cost and effort.
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. ; Georgia Institute of Technology. School of Aerospace Engineering

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.
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. ; Georgia Institute of Technology. School of Aerospace Engineering

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.
Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors

(Georgia Institute of Technology, 2013-04) Wu, Allen D. ; Johnson, Eric N. ; Kaess, Michael ; Dellaert, Frank ; Chowdhary, Girish ; Georgia Institute of Technology. College of Computing ; Georgia Institute of Technology. School of Interactive Computing ; Georgia Institute of Technology. Center for Robotics and Intelligent Machines ; Georgia Institute of Technology. School of Aerospace Engineering ; Massachusetts Institute of Technology

A vision-aided inertial navigation system that enables autonomous flight of an aerial vehicle in GPS-denied environments is presented. Particularly, feature point information from a monocular vision sensor are used to bound the drift resulting from integrating accelerations and angular rate measurements from an Inertial Measurement Unit (IMU) forward in time. An Extended Kalman filter framework is proposed for performing the tasks of vision-based mapping and navigation separately. When GPS is available, multiple observations of a single landmark point from the vision sensor are used to estimate the point’s location in inertial space. When GPS is not available, points that have been sufficiently mapped out can be used for estimating vehicle position and attitude. Simulation and flight test results of a vehicle operating autonomously in a simplified loss-of-GPS scenario verify the presented method.
Real-time Implementation and Validation of a New Hierarchical Path Planning Scheme for UAVs via Hardware-in-the-Loop Simulation

(Georgia Institute of Technology, 2009) Jung, Dongwon ; Ratti, Jayant ; Tsiotras, Panagiotis ; Georgia Institute of Technology. School of Aerospace Engineering

We develop a hierarchical path planning and control algorithm for a small fixed-wing UAV. Incorporating the hardware-in-the-loop (HIL) simulation environment, the hierarchical path planning and control algorithm has been validated through on-board, real-time implementation on a small autopilot. We present two distinct real-time software framework for implementation of the overall control algorithms including path planning, path smoothing, and path following. We especially emphasize the use of a real-time kernel, which shows effectiveness and robustness in accomplishing non-trivial real-time software environment. By a seamless integration of the control algorithms with a help of real-time kernel, it has been demonstrated that the UAV equipped with a small autopilot having limited computational resources manages to autonomously accomplish the mission control objective of reaching the goal while avoiding obstacles without human intervention.
Visibility Cues for Communication Aware Guidance in Cluttered Environments

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

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.
Design and Development of a Low-Cost Test-Bed for Undergraduate Education in UAVs

(Georgia Institute of Technology, 2005) Jung, Dongwon ; Jevy, E. J. ; Zhou, D. ; Fink, Richard W. ; Moshe, J. ; Earl, A. ; Tsiotras, Panagiotis ; Georgia Institute of Technology. School of Aerospace Engineering

This article describes the efforts undertaken at the School of Aerospace Engineering at the Georgia Institute of Technology for the development of a low-cost Unmanned Aerial Vehicle (UAV) test-bed for educational purposes. The objective of this test-bed is to provide an avenue for the involvement of undergraduate students (primarily) and graduate students (secondarily) in UAV research. The complete design and development of all hardware interfaces of the UAV platform including the on-board autopilot is presented. Based on flight test data a linear model has been developed for the lateral and longitudinal dynamics.
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 ; Georgia Institute of Technology. School of Aerospace Engineering ; Georgia Institute of Technology. Unmanned Aerial Vehicle Research Facility

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.
The Semi-Coaxial Multirotor

( 2018-05) Bershadsky, Dmitry ; Haviland, Stephen ; Johnson, Eric N. ; Georgia Institute of Technology. School of Aerospace Engineering

The ”semi-coaxial” multirotor configuration is presented including its advantages over the conventional coaxial rotor configuration. The semi-coaxial configuration retains the benefits of the coaxial configuration, and additionally alleviates the loss of efficiency encountered when rotors are stacked coaxially. In addition to being more power-efficient than the standard coaxial configuration, the described configuration allows for nearly- or fully-actuated control of a multirotor when used in configurations such as the three-armed Y6 hexarotor. Using this configuration, a new Direct Force Control (DFC) multirotor is presented: the Y6sC, a specific example of the semi-coaxial multirotor. The configuration orients six rotors in a way which allows the vehicle to hover in non-zero attitudes and translate without rotating with higher efficiency than the corresponding coaxial design.
Hierarchical motion planning with kinodynamic feasibility guarantees: Local trajectory planning via model predictive control

(Georgia Institute of Technology, 2012-05) Cowlagi, Raghvendra V. ; Tsiotras, Panagiotis ; Georgia Institute of Technology. School of Aerospace Engineering ; Georgia Institute of Technology. Institute for Robotics and Intelligent Machines

Motion planners for autonomous vehicles often involve a two-level hierarchical structure consisting of a high-level, discrete planner and a low-level trajectory generation scheme. To ensure compatibility between these two levels of planning, we previously introduced a motion planning framework based on multiple-edge transition costs in the graph used by the discrete planner. This framework is enabled by a special local trajectory generation problem, which we address in this paper. In particular, we discuss a trajectory planner based on model predictive control for complex vehicle dynamical models. We demonstrate the efficacy of our overall motion planning approach via examples involving non-trivial vehicle models and complex environments, and we offer comparisons of our motion planner with state-of-the-art randomized sampling-based motion planners.