Autonomous Control Of A Hybrid Unmanned Aerial Towed System On A Moving Platform, Zachary M. Miller

Graduate Theses and Dissertations (2019 - present)

With tethered rotor drones being more popular for aerial surveillance, moving platforms for tethered drones are being researched. However, these systems require constant power to the rotor drones for stabilization. With this difficulty in power consumption, a hybrid drone solution is presented. The hybrid drone is similar to an airplane, with quadcopter motors attached for stabilization and thrust when not moving.

The controller for the hybrid drone was tested and verified in simulation. The simulation of the system was built in Fortran and consists of a driver, a tether, and a hybrid drone. The driver was modeled after a generic …

Implementation Of Unscented Kalman Filter-Based State Estimation For Multiple Spacecraft Using Global Positioning System Measurements, Bala Prenith Reddy Gopu

Theses and Dissertations

This study presents an implementation of state estimation for a drag-based rendezvous mission involving multiple chaser spacecraft and a single target, using Unscented Kalman Filtering (UKF) with Global Positioning System (GPS) measurements. The implemented method combines GPS navigation solutions with UKF to provide real- time state estimates of all spacecraft involved. Nonlinear least squares method is employed to process pseudorange and pseudorange rate measurements to determine receiver states, UKF utilizes these states as measurements to estimate absolute space- craft positions and velocities. This implementation also addresses practical challenges including raw GPS measurement processing, and varying GPS satellite geometries.

Campus Navigator: A Mobile App For Seamless University Navigation, Hafsa Mohammed, Ali Rahimzadehfard, Rachab Wilson, Mathias Rossi, Turaj Ashuri, Amir Ali Amiri Moghadam

Symposium of Student Scholars

Navigation services play a big role in everyone’s daily lives, from directing them on new roads to guiding them through buildings. Outdoor navigation services have evolved from physical maps to digital ones like Google Maps for ease of use and accessibility. Upon conducting literature research, the team found that many navigation apps lack clear and accurate instructions for how to navigate university campuses such as Marietta campus. Due to the size of KSU’s Marietta campus and its buildings, effortless navigation has been a common challenge for students, faculty, and visitors alike. Additionally, all buildings are referred to by letters, numbers, …

Utilizing Augmented Reality For Immersive Space Mission Design, Joseph Anderson

Doctoral Dissertations and Master's Theses

Designing spacecraft mission trajectories is a complex, tedious, and stringent process that requires a strong background in astrodynamics and programming due to the complex dynamical environment of space. The current 2D visualization methods for displaying these geometrically abstract trajectories make it difficult to understand the true nature of more complex orbits. Advancements in immersive headsets and their intuitive interaction capabilities make them ideal for solving and understanding 3D problems that require complex spatial representations, revealing an innovative and unique opportunity for the astrodynamics and space mission planning field. This effort covers the development of an immersive space mission design tool …

L2 Certification Rocket Launch, Seungyou Cho

SACAD: Scholarly Activities

The LOC 835 high-power rocket with J275W-12 motor at Argonia, KS, for L2 certification, was auspiciously launched and returned. J means the motor can exert 640-1280 Ns of impulse, which makes a sizeable propelling sound. Even though four main hindrances occurred from the construction to the launch, the issues were revised correctly. The rail button and the tracker were severe issues, so I devised the method of drilling a hole for the rail button, but there was no way to replace a broken tracker. The wind speed on the launch day was so strong that the rocket flew 1-2 miles …

Adaptive Control Of Thrusters To Account For Deficiencies In Actuator Effectiveness And Model Uncertainties, Matthew Stanko

Doctoral Dissertations and Master's Theses

Future space missions are expected to become ever more ambitious and challenging. A successful mission requires advanced and resilient control algorithms that enable missions, such as satellite refueling, on-orbit inspection, and end-of-life servicing. This thesis explores the development and application of robust and adaptive control laws for an over-actuated spacecraft system with 3 degrees of freedom (DoF) to mitigate the effects of actuator deficiencies and system uncertainties. Additionally, the nature of the system being over-actuated allows for particular actuator degradation and failure. For stability and command tracking, a novel controller is designed and augmented with sliding mode control, adaptive control, …

Coupled Dynamics In The Cislunar Region And Spacecraft Attitude Prediction In A Higher-Fidelity Model​, Annika Anderson

Doctoral Dissertations and Master's Theses

The cislunar region of space is a complex, multi-body dynamical environment that cannot be modeled trivially. Traditional point-mass assumptions made to simplify the mission design process may be insufficient for accurately predicting spacecraft motion in environments where orbit-attitude coupling is non-negligible. One of the most famous of such models is the circular restricted three-body problem. This thesis advances the state of the art in astrodynamics by modeling all bodies in the problem as rigid bodies, allowing for spacecraft orientation to be propagated and considered. Two models are under consideration—the circular restricted full three-body problem (CRF3BP) and a full higher-fidelity ephemeris …

Machine Learning Methods For Hypervelocity Fragment Flyout Characterization, Katharine Larsen

Doctoral Dissertations and Master's Theses

Resulting from breakup events, such as collisions and explosions, hypervelocity fragments create potential hazards for both terrestrial and on-orbit environments, such as terrestrial weapons explosions and satellite breakup events, respectively. To avoid unnecessary damage, an accurate understanding or characterization of hypervelocity fragmentation events is vital. Currently, publicly available two-line elements collected from on-orbit breakup events are limited, excluding pre-detonation parent body conditions, such as orientation, and information of smaller fragments. The uncertainty of these datasets varies between each collected set. Therefore, the overall goal of this work is to employ machine learning to estimate distribution characteristics of a space debris …

Stability Limits Of Uncertain Systems In The Presence Of Unmatched Coupled Dynamics And Actuator Dynamics With Adaptive Architectures, Bronson Saulo

Doctoral Dissertations and Master's Theses

Uncertain systems with coupled dynamics and actuator dynamics are prevalent in various applications spanning private, commercial, and government sectors. While stabilization and command tracking strategies exist, they often rely on idealized assumptions, such as negligible actuator bandwidth limitations and matched coupled dynamics. In order to mitigate actuator-induced limitations, we first employ standard model reference adaptive control (MRAC) architectures. We then proposed two architectures: modified hedging reference modeled based MRAC and modified expanded reference model based MRAC. In order to deal with coupled dynamics, we used an observer design to estimate the states of unmatched coupled dynamics. In addition, Lyapunov stability …

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, 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), 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 …

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, 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, 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.

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.

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, V_P and V_E, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ =  V_E/V_P > 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 …

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.

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, 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, 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, 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, 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 …

Design And Simulation Of An Ai-Powered Autonomous Quadrotor Framework For Search And Rescue Operations, James J. Shope

Graduate Theses, Dissertations, and Problem Reports (ETD)

Unmanned aerial vehicles (UAVs), particularly quadrotor platforms, have proven to be indispensable tools for search and rescue (SAR) teams due to their maneuverability, rapid deployment, and affordable operation. The current SAR use cases of quadrotors span from aerial surveillance to mission planning and strategic deliveries. However, most SAR applications remain passive or semi-autonomous, such that they rely on human-operated control or data assessment. Advancements in autonomous control strategies bring about a future where a single SAR operator can program and deploy several UAVs. This thesis details the development and simulation of a fully autonomous, AI-powered quadrotor framework capable of detecting …

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.

End-To-End Neural Network Based Optimal Control For Asymmetric Quadrotor Uas, Ross O'Hara

Graduate Theses, Dissertations, and Problem Reports (ETD)

This thesis presents the development and evaluation of a neural network-based optimal controller for asymmetrically loaded quadrotor unmanned aerial systems (UAS). Traditional control strategies such as PID are typically designed under symmetry assumptions and often degrade in performance when faced with significant loading asymmetries. To address this, a six-degree-of-freedom quadrotor model incorporating rotor dynamics and center-of-mass offsets was developed. A trajectory optimization framework using MATLAB’s fmincon solver generated over 50,000 energy-optimal trajectories across symmetric and asymmetric conditions. These were used to train a range of feedforward neural network architectures in a full-factorial study.

The best-performing controller was identified, having five …

Physics-Informed Neural Network Based Aerodynamic Modeling Framework, Nathaniel E. Michek

Graduate Theses, Dissertations, and Problem Reports (ETD)

Significant advances have been made in developing aerodynamic models over the years. While these advances span many modeling techniques and data collection methods, certain aerodynamic regimes still pose significant challenges. These regimes commonly occur when an aerodynamic body is under extreme flight conditions. Many of these conditions occur simultaneously in the rare and poorly understood case of a tumbling aerodynamic body. The flight of a tumbling aerodynamic body goes through the entire range of aerodynamic angles, alpha and beta, causing significant non-linearities and time-dependent effects associated with flow separation. During tumbling, the aerodynamic body simultaneously rotates about all three axes …

Evaluation Of Small Unmanned Tailsitter Hybrid Air Vehicles Via Full Flight Simulation, Andrew Spencer Winters

Graduate Theses, Dissertations, and Problem Reports (ETD)

Small Unmanned Aerial Vehicles have exploded in popularity in the past 15 years among researchers and for industrial uses such as agriculture, search and rescue, and infrastructure inspection. Fixed wing and multirotor designs present two major paths that can be taken with these technologies. Fixed wing platforms have superior aerodynamic efficiency but require large areas for takeoff/landing and cannot hold a constant position in space, limiting their use. Multirotor configurations offer a more versatile platform that can maneuver in 3 dimensions independently but lack the endurance of fixed wing vehicles. This thesis analyses a quadrotor biplane and a variable wingspan …

Parameter Estimation Of A 100 Seater Simulated Passenger Aircraft, Michael James Winston

Graduate Theses, Dissertations, and Problem Reports (ETD)

Virtual flight test aircraft provide good opportunities to test new parameter estimation methods. However, good estimates for the parameters in VIRTTAC Castor, a virtual test aircraft, are unavailable. This thesis uses two well-established time domain methods, the Output Error Method and the Filter Error Method, to estimate the parameters of VIRTTAC Castor. Three standard maneuvers were used: Elevator 3-2-1-1, Rudder Doublet, and Aileron Multi-Step. The parameters were estimated across three different flight conditions: weight, altitude and air speed, which resulted in 27 tests for each maneuver. All parameters, and standard deviations estimated are included in the appendix as a table.

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