Dual Quaternions For Gravity Recovery Missions,
2025
Embry-Riddle Aeronautical University
Dual Quaternions For Gravity Recovery Missions, Ryan Kinzie
Doctoral Dissertations and Master's Theses
A dual quaternion-based modeling, state estimation and control approach is introduced as a better alternative to the traditional methods which are currently utilized for gravity recovery missions. The proposed modeling and control approach was verified against and compared to the tangent bundle to Special Euclidean Group 3 through MATLAB simulations. The dual quaternion-based approach shows superior performance over traditional linearized and uncoupled methodologies, in both modeling accuracy of spacecraft translational position, and the ability to control the pose of a test mass relative to its host spacecraft. Utilizing data products from the Gravity Recovery and Climate Experiment Follow-On mission, a …
Modeling The Dynamics Of Flexible Aerospace Vehicles Using The Theory Of Functional Connections,
2025
Embry-Riddle Aeronautical University
Modeling The Dynamics Of Flexible Aerospace Vehicles Using The Theory Of Functional Connections, Carlo Lombardi
Doctoral Dissertations and Master's Theses
Modeling and control of flexible vehicles is a topic of high interest in the aerospace field and a key challenge lies in finding accurate mathematical representations of the flexible dynamics of continuous elastic structures that allow simple integration into estimation and control algorithms. The answer was found in approximating the dynamics of these systems with sets of coupled Ordinary Differential Equations (ODE) for which a well-established estimation and control theory is available. Each of the techniques employed to achieve this goal is characterized by its own strengths and limitations. Hence, the main objective of this research is to develop the …
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3),
2025
Embry-Riddle Aeronautical University
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal
Doctoral Dissertations and Master's Theses
Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …
Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems,
2025
University of South Alabama
Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya
Shelby Hall Graduate Research Forum Presentations
Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.
Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling,
2025
Air Force Institute of Technology
Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones
Theses and Dissertations
The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.
Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments,
2025
Air Force Institute of Technology
Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty
Theses and Dissertations
This thesis addresses the challenge of generating optimized UAV waypoints for complete coverage of complex 3D environments, utilizing graph-based computational techniques. The proposed framework replaces computationally intensive steps—triangulation and three-coloring—within the Vantage Waypoint Set Generation Algorithm (VWSGA) pipeline with Graph Neural Networks (GNNs). By learning structural patterns, the GNN achieves scalable and robust triangulation and node classification, enabling enhanced coverage planning in irregular geometries. A novel penalty mechanism ensures alignment with graph structure during adjacency prediction. Experimental results demonstrate the effectiveness of GNNs in balancing accuracy, computational efficiency, and adaptability, advancing UAV coverage optimization.
Autonomous Vehicle Path Planning Under Uncertainty,
2025
Air Force Institute of Technology
Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan
Theses and Dissertations
Autonomous vehicles are increasingly being deployed for use in high-stakes and uncertain environments where safe and efficient navigation is critical. In these scenarios, traditional path planning approaches, which rely primarily on deterministic models and fixed assumptions, fall short due to the inherent uncertainty of dynamic threats, sensor inaccuracies, and incomplete information. This research addresses these challenges by developing a novel path-planning methodology that combines the Chance-Constrained Rapidly Exploring Random Tree* (CC-RRT*) algorithm with a probabilistic risk assessment heuristic. This method models uncertainty in sensor detection zones, obstacles in the environment, and the Autonomous Vehicle itself, which allows for uncertainty during …
Visual Segmentation For Autonomous Aircraft Landing On Austere Runways,
2025
Air Force Institute of Technology
Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens
Theses and Dissertations
Autonomous aircraft must land without human intervention, but existing methods rely on GPS or marked runways, which may be unavailable in austere environments. This paper presents a vision-based approach using semantic segmentation to detect runways and estimate aircraft pose by comparing camera and satellite imagery. We detail the model’s training and demonstrate its effectiveness with simulated and real UAV data.
An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture,
2025
Air Force Institute of Technology
An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow
Theses and Dissertations
This paper is concerned with a co-planar pursuit-evasion scenario where two Pursuers (P) are after an Evader (E). The players are holonomic/can turn on a dime and their speeds, VP and VE, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ = VE/VP > 1. The Pursuers are endowed with a circular capture disc whose radius l > 0. A differential game (DG) with three states and one parameter is addressed through geometric and analytical methods where a partial solution is outlined and visualized. The game is split …
Metaheuristic Techniques To Optimize Trajectory Planning Of Uav Swarms: Enhancing Data Acquisition In Wireless Sensor Networks,
2025
American University in Cairo
Metaheuristic Techniques To Optimize Trajectory Planning Of Uav Swarms: Enhancing Data Acquisition In Wireless Sensor Networks, Nada Ali Mohamed Ahmed Ahmed
Theses and Dissertations
Unmanned aerial vehicles (UAVs) have become increasingly integrated into various applications due to their cost-efficiency, rapid deployment, flexible maneuvers, and enhanced performance. This has led to the development of a new field called UAV-assisted Wireless Sensor Networks (U-WSNs), which focus on data routing, network performance optimization, and planning UAV trajectories between sensor nodes in wireless sensor networks. In this thesis, a new framework has been proposed to manage a swarm of UAVs cooperatively serving large-scale wireless sensor networks. The framework consists of three optimization problems: distributing sensor nodes among UAVs, finding optimal trajectories in the presence of obstacles, and performing …
Multi-Agent Differential Games Under An Altruistic Equilibrium,
2025
University of Texas at Arlington
Multi-Agent Differential Games Under An Altruistic Equilibrium, Craig Alan Lovell
Mechanical and Aerospace Engineering Theses - Archive
This work studies a multi-agent differential game with linear dynamics under the Berge equilibrium. The governing coupled differential equations for a two-agent and a three-agent game under the Berge equilibrium are derived. These games are simulated and compared to the Nash equilibrium. A sensitivity study is performed which validates that, under some criteria, the Nash equilibrium can be recovered from the Berge equilibrium. Policy fusion between the Berge and Nash equilibrium is explored in a two-agent game. A five-agent game under the Berge equilibrium is simulated and multiple teams of agents in this game are evaluated. Finally, a mixed game, …
Mass-Adaptive Admittance Control For Robotic Manipulators,
2025
Old Dominion University
Mass-Adaptive Admittance Control For Robotic Manipulators, Hossein Gholampour, Jonathon E. Slightam, Logan E. Beaver
Mechanical & Aerospace Engineering Faculty Publications
Handling objects with unknown or changing masses is a common challenge in robotics, often leading to errors or instability if the control system cannot adapt in realtime. In this paper, we present a novel approach that enables a six-degrees-of-freedom robotic manipulator to reliably follow waypoints while automatically estimating and compensating for unknown payload weight. Our method integrates an admittance control framework with a mass estimator, allowing the robot to dynamically update an excitation force to compensate for the payload mass. This strategy mitigates end-effector sagging and preserves stability when handling objects of unknown weights. We experimentally validated our approach in …
Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks,
2025
Sandia National Laboratories
Optimal Manipulation Motion Action Planner Enabled By Physics Informed Neural Networks, Jonathon E. Slightam, Logan E. Beaver
Mechanical & Aerospace Engineering Faculty Publications
Autonomous robotic manipulation in unstructured environments faces many challenges and is hindered by capabilities that bridge the gap between perception and acting on the world. Action plans that are centric to object motion rather than end-of-arm tooling behavior may aid this. This paper presents an autonomous action planner for a feedback linearizeable system comprised of three base motions that can be leveraged on their own or in combination to give custom motion plans. The optimization routine for the three different types of motion are presented, which are integrated into physics informed neural networks. A component of this is the autonomy …
Simulation-To-Hardware Validation Of Mpc For Binary Thruster 2d Cubesat Control,
2025
University of Kentucky
Simulation-To-Hardware Validation Of Mpc For Binary Thruster 2d Cubesat Control, Aevar Amundinusarson Oefjoerd
Theses and Dissertations--Mechanical and Aerospace Engineering
Small satellites must execute precise, fuel-limited maneuvers under strict actuation and operational constraints. Model Predictive Control (MPC) is a suitable approach because it optimizes future actions while explicitly enforcing these limits. This work evaluates (1) whether MPC can operate in real time using binary (on/off), asymmetric thrusters, and (2) whether a high-fidelity digital twin can be used to tune and validate the controller prior to hardware testing.
An MPC framework was implemented on a planar satellite prototype that floats on air bearings, operates at 16.7 Hz (60 ms period), and uses eight binary thrusters exhibiting up to 13.2% variation in …
Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System,
2025
The University of Akron
Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System, Dimitry Melnikov, Evan Bartel, Andrew Burrier, Goran Gjorgievski
Williams Honors College, Honors Research Projects
NASA's Artemis program requires precise navigation capabilities to establish the first sustained presence on the lunar surface. However, as launches bring necessary orbital infrastructure, the Artemis program will face a critical period during which reliable lunar navigation is not possible. To address this challenge, the V.E.C.T.O.R. system tracks assets, such as rovers and astronauts, as User Terminals relative to a pre-existing cell tower, or Base Station. To do so, the system leverages existing Base Station hardware to calculate the location of User Terminals in conjunction with existing communications infrastructure.
An Operational Field Study: A Comparison Of Piloting Uncrewed Underwater Vehicles And Uncrewed Aircraft Systems,
2025
Embry-Riddle Aeronautical University
An Operational Field Study: A Comparison Of Piloting Uncrewed Underwater Vehicles And Uncrewed Aircraft Systems, David Thirtyacre, Joseph Cerreta, Pete Miller, Kimberly Luthi, Jolee Thirtyacre
Publications
and operations, the ability to cross-train personnel in both Uncrewed Underwater Vehicles and Small Uncrewed Aircraft System operations has become a focal point for efficiency and workforce optimization. This study presents a comparative analysis of the operational and human factor considerations involved in piloting mini UUV and sUASs, highlighting the key similarities and differences in control methods, environmental influences, navigation, emergency procedures, and situational awareness. A qualitative experimental field study was conducted between July 2024 and October 2024, involving real-world deployments of both systems in maritime and aerial environments. Findings indicated that while UUV and sUAS operators relied on remote …
Investigation Of A Busemann Intake At Negative Angle Of Attack,
2025
Purdue University
Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell
Publications
A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …
The Interacting Roles Of Attention Allocation And Trust In Highly Automated Aam Environments,
2025
Old Dominion University
The Interacting Roles Of Attention Allocation And Trust In Highly Automated Aam Environments, Yusuke Yamani
Psychology Faculty Publications
[First slide]
Mechanisms of attentive visual processing
- Attention control
- Visual search
- Eye movement
- Aging and individual differences
Limits of human performance in applied environment
- Complex displays
- Machine operation
- Surface transportation
- Advanced air mobility
- Nuclear operation
Methods to ameliorate human cognitive performance
- Human-machine interface
- Human autonomy/AI teaming
- Human-systems integration
- Training
Potential Of Lidar And Hyperspectral Sensing For Overcoming Challenges In Current Maritime Ballast Tank Corrosion Inspection,
2025
Old Dominion University
Potential Of Lidar And Hyperspectral Sensing For Overcoming Challenges In Current Maritime Ballast Tank Corrosion Inspection, Sergio Pallas Enguita, Jiajun Jiang, Chung-Hao Chen, Samuel Kovacic, Richard Lebel
Electrical & Computer Engineering Faculty Publications
Corrosion in maritime ballast tanks is a major driver of maintenance costs and operational risks for maritime assets. Inspections are hampered by complex geometries, hazardous conditions, and the limitations of conventional methods, particularly visual assessment, which struggles with subjectivity, accessibility, and early detection, especially under coatings. This paper critically examines these challenges and explores the potential of Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) to form the basis of improved inspection approaches. We discuss LiDAR’s utility for accurate 3D mapping and providing a spatial framework and HSI’s potential for objective material identification and surface characterization based on spectral …
Navigating Together: The Conav Testbed And Framework For Benchmarking Cooperative Localization,
2025
University of Cincinnati
Navigating Together: The Conav Testbed And Framework For Benchmarking Cooperative Localization, Rohith Boyinine, Jayanth Ammapalli, Anusna Chakraborty, Rajnikant Sharma, Kevin Brink, Clark N. Taylor
Faculty Publications
This paper presents CoNaV, a comprehensive framework for creating a multi-vehicle cooperative localization (CL) testbed designed to support the benchmarking, development, and deployment of cooperative navigation algorithms. Given the essential role of CL in improving localization accuracy for both defense and civilian applications, CoNaV provides a robust environment for rigorously validating algorithms under real-world conditions. By establishing a benchmark for CL algorithms, CoNaV lays a foundation for advancing research into more sophisticated and distributed CL solutions. This framework highlights the potential of cooperative navigation to enhance multi-vehicle operations and offers a scalable, practical approach for future developments in CL technology.
