Navigation, Guidance, Control and Dynamics Commons^™

Implementation Of Path Planning Methods To Detect And Avoid Gps Signal Degradation In Urban Environments, Ayush Raminedi

Doctoral Dissertations and Master's Theses

In the modern world, various missions are being carried out under the assistance of autonomous flight vehicles due to their ability to operate in a wide range of flight conditions. Regardless, these autonomous vehicles are prone to GPS signal loss in urban environments due to obstructions that cause scintillation, multi-path, and shadowing. These effects that decrease the GPS functionality can deteriorate the accuracy of GPS positioning causing losses in signal tracking leading to a decrease in navigation performance. These effects are modeled into the simulation environment and are used as part of the path planning algorithm to provide better navigation …

Prediction Of Handling Qualities Deficiencies For Advanced Air Mobility Aircraft, Louis Spier

Doctoral Dissertations and Master's Theses

To date, there are hundreds of Advanced Air Mobility (AAM) vehicles under development. Most of these vehicles differ significantly from traditional airplanes and rotorcraft when it comes to configuration and handling qualities. Handling qualities for traditional airplanes and rotorcraft are often very predictable. All AAM concepts currently under development feature some sort of fly-by-wire flight control system. Regulatory agencies already have decades of experience with certifying fly-by-wire airplanes. Fly-by-wire rotorcraft have proven to be significantly more difficult to certify and several flight test accidents have occurred as a result of handling qualities deficiencies, or “cliffs”. To ensure the safe and …

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …

Trustable Adaptive Controllers For Multi-Agent Systems With Actuator Dynamics, Atahan Kurttisi

Doctoral Dissertations and Master's Theses

Multi-agent systems have become a powerful tool for a wide range of applications due to the effective and cheap solutions they offer. Especially during the last decade, they have impacted a wide array of civilian and military applications (e.g., surveillance, reconnaissance, and payload transportation). However, they suffer system anomalies due to the operational and material conditions, which yields degraded performance or even instability. Hence, this dissertation investigates the distributed adaptive control design process for uncertain multi-agent systems with scalar and high-order dynamics in the presence of unknown control effectiveness and actuator dynamics. First, it provides an approach for driving a …

Adaptive Control Of An Aeroelastic System For Active Flutter Suppression And Disturbance Rejection, Patrick Sterling Downs

Doctoral Dissertations and Master's Theses

The future of aircraft design strives for lighter weight, more aerodynamically efficient structures. These improvements may come with the drawback of increased structural flexibility and elevated aeroelastic effects, often resulting in a lower flutter speed. This motivates the implementation of advanced control methods to control aeroelastic systems over a range of flight conditions, suppress and delay the onset of flutter, and compensate for disturbances, actuator dynamics, and unmodeled nonlinear dynamics.

This dissertation first develops a novel method for constructing time-domain simulation models of two and three-dimensional aeroelastic systems, resulting in models that are suitable for the implementation of state-space control …

Adaptive Control For A Class Of Nonlinear, Time Varying Rotational Systems, John Zelina

Doctoral Dissertations and Master's Theses

Aerospace systems often exhibit nonlinear, time varying dynamics. Expansive mission profiles, fuel burn or transfer and payload deployments or slung loads can supply additional complexity that can excite the plant dynamics and result in undesirable performance. Because of these often unknown dynamical effects in aerospace systems, an emphasis is placed on controller robustness as significant safety risks are present. Due to the difficulty of predicting uncertainties, robust control can be achieved in two distinct ways. The first approach is to design a control law to be tolerant to a large amount of uncertainty, and the second is to design a …

Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico, Jose Cabrera, Blake Neal, Kevin Adkins, Ronny Schroeder, Gwendolyn Klenke, Shannon Brines, Nayethzi Hernandez, Kevin Li, Riley Glancy, Ivette Perfecto

Publications

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and …

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …

Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen

Faculty Publications

It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …

Cubesat Reaction Wheel Attitude Control Platform System Architecture, Justin Hartland

Beyond: Undergraduate Research Journal

In the classroom, physics behind spacecraft attitude dynamics and controls is abstract and difficult to comprehend. It is common that students struggle to develop the connection between the math they learn and how it can be applied in the real world. The goal of this project is to design and manufacture a 1U, 3U, and 6U CubeSat testbed for autonomous control systems utilizing reaction wheels. The testbed will include three separate reaction wheels each mounted on its own respective axis to control the attitude in 3 degrees of freedom. The end goal of the CubeSat Control Platform is to be …

Aerospace Vehicle Navigation And Control System Comprising Terrestrial Illumination Matching Module For Determining Aerospace Vehicle Position And Attitude, Liberty M. Shockley, Robert A. Bettinger

AFIT Patents

The present invention relates to an aerospace vehicle navigation and control system comprising a terrestrial illumination matching module for determining spacecraft position and attitude. The method permits aerospace vehicle position and attitude determinations using terrestrial lights using an Earth-pointing camera without the need of a dedicated sensor to track stars, the sun, or the horizon. Thus, a module for making such determinations can easily and inexpensively be made onboard an aerospace vehicle if an Earth-pointing sensor, such as a camera, is present.

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Optimizing Multi-Agent Network For Target Localization Through Mutual Information Maximization, Bibek Adhikari

Mechanical and Aerospace Engineering Theses - Archive

A multi-agent network is a system comprising multiple interacting agents that coexist collaboratively within a networked, autonomous environment. The thesis addresses the target localization problem using a multi-rover network, described as autonomous agents, using an information-theoretic distributed control framework. The objective of the mission, through the integration of the particle filter representation of the posterior probability distribution of the target state and the observable, is to compute control input to arrange agents’ locations, maximizing the mutual information between the target’s position and sensor measurements. Consequently, the method leads to future observation which minimizes the future uncertainty of the target state. …

Cooperative Navigation In Gps-Denied Environments Using Visual Simultaneous Localization And Mapping (Slam), Rakesh Yadav

Mechanical and Aerospace Engineering Theses - Archive

In this thesis, an application of RTAB-Map’s visual SLAM (Simultaneous Localization and Mapping) is used to explore autonomous cooperative navigation in GPS-denied environment using a rover and a quadrotor. The primary objective is to enhance cooperative navigation by allowing the rover and the drone to guide each other using the maps constructed or generated by them. The map is generated using the RTAB-Map SLAM technique using stereo camera only. The thesis addresses three major issues: quality of map created by UAV and UGV, the visual odometry drift, and the robustness of the cooperative framework in the static and dynamic environment. …

Study Of A Multi-Agent Containment Problem Under Communication Constraints And Defense From Malicious Agents, Braulio Mora

Mechanical and Aerospace Engineering Theses - Archive

This thesis investigates a multi-agent containment problem where a fast evader, moving at a constant speed and heading, attempts to escape a circular containment region. A team of slow pursuers possess a nonzero capture radius and seek to capture the evader before escape. The research addresses two primary scenarios: one involving the team of pursuers, with no communication network, being constrained to the edge of the containment region, and the second involving a team of pursuers, with a communication network, not being constrained to the edge of the containment region. Both scenarios study the influence of malicious agents in the …

Nonlinear Guidance And Control Of Unmanned Aerial Manipulators For Delivering A Payload On A Moving Platform, Ravi Gyawali

Mechanical and Aerospace Engineering Theses - Archive

Unmanned Aerial manipulators (UAMs) are a class of Unmanned Aerial Vehicles (UAVs) equipped with a manipulator. By combining the aerial mobility of a UAV with a manipulator's dexterity, these hybrid systems can perform a wide range of complex tasks while reducing risks and costs. As a result, they are increasingly being utilized for military, industrial, and agricultural applications.

The thesis presents a novel approach for a multi-UAM system to collaboratively deliver a payload on a stationary or maneuvering platform. A sliding-mode-based guidance law, sourced from existing literature, is integrated with a combined control technique for the UAVs and their respective …

A New Trajectory In Uav Safety: Leveraging Reinforcement Learning For Distance Maintenance Under Wind Variations, Xiaolin Xu, Jeffrey Sun

Journal of Aviation/Aerospace Education & Research

In the field of aviation, safety is a critical cornerstone, and the operation of Unmanned Aerial Vehicle (UAV) systems is deeply connected with this principle. A thorough analysis and rigorous simulation and testing of aircraft systems are essential to avoid severe safety hazards. This paper delves into the safety issue in UAV operations, specifically regarding maintaining minimum safety distances under fluctuating wind conditions. The study introduces a novel solution based on a Deep Deterministic Policy Gradient (DDPG) model, a reinforcement learning method. The DDPG model was trained using a simulated environment created through the Gazebo simulator, with values for wind …

Forced Displacement Technique For Measuring Blunt Body Aerodynamics In A Magnetic Suspension Wind Tunnel, Mark Schoenenberger, David Cox, Colin Britcher, Caleb Hull

Mechanical & Aerospace Engineering Faculty Publications

The Old Dominion University/NASA Langley 6-Inch Magnetic Suspension Wind Tunnel has developed the ability to levitate blunt bodies which can oscillate freely about the yaw axis. This allows for the measurement of static and dynamic stability coefficients without sting interference. The magnetic suspension controller introduces other translational forces which affect the vehicle dynamics complicating data reduction. Exciting model oscillations in a reliable way has also been a challenge. A new test method has been developed that produces capsule oscillations from forced oscillatory translational motion at the resonant yaw oscillatory frequency of the capsule. After oscillations are excited, the translational forcing …

Cooperative Pursuit Nonlinear Guidance And Control Laws To Surround Intruder Swarms, Rishab Rijal

Mechanical and Aerospace Engineering Theses - Archive

In this thesis, an integrated guidance and control architecture to enable a group of n quadcopters, which are connected to each other by a rope line, to perform cooperative pursuit with the objective to surround a swarm of intruder UAVs (possibly flying in restricted airspaces) is presented. The UAVs in the intruder swarm may maneuver and sometimes get closer to each other, and sometimes further apart, and the pursuing UAVs need to adjust their formation appropriately to achieve the surround objective. A nonlinear controller is developed for the quadcopters so as to effectively execute the guidance laws, thereby ensuring precise …

On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard

Graduate Theses, Dissertations, and Problem Reports (ETD)

As robots adopt more real world responsibilities, they will be expected to solve more complicated problems. In some cases limited prior knowledge will result in unmodelled environmental conditions; in others, multiple users may have competing perspectives on how to frame a decision problem. Many existing frameworks, namely Markov decision processes (MDP) presuppose users have identified a specific problem with models sufficient to solve or learn a problem. If we wish to extend MDPs to novel problems or those heavily dependent on user feedback, autonomous decision makers must be able to identify limitations in how a given problem is framed and …

Adaptive Control Of Vscmgs For Satellite Attitude Tracking, Kyle Vernyi

Doctoral Dissertations and Master's Theses

The democratization of space has brought about many new opportunities and challenges for industry, academia, and governments. Smaller and more affordable platforms are now regularly being launched. These platforms have higher uncertainty due to cost, engineering constraints, unmodeled dynamics, coupled effects, and the challenging space environment. In addition, both mission requirements and complexity are simultaneously being increased. In order to achieve these requirements, new satellite control algorithms are required. Adaptive control offers a strong solution to the uncertainty problem. This thesis develops several adaptive control algorithms for satellites equipped with momentum management devices. Momentum management devices such as reaction wheels …

Embedded State Estimation For Optimization Of Cislunar Space Domain Awareness Constellation Design, Thomas Henry Clareson

Graduate Theses, Dissertations, and Problem Reports (ETD)

The traffic in cislunar space is expected to increase over the coming years, leading to a higher likelihood of conjunction events among active satellites, orbital debris, and non-cooperative satellites. This increase necessitates enhanced space domain awareness (SDA) capabilities that include state estimation for targets of interest. Both Earth surface-based and space-based observation platforms in geosynchronous orbit or below face challenges such as range, exclusion, and occlusion that hinder observation. Motivated by the need to place space-based observers in the cislunar space regime to overcome these challenges, this paper proposes a cislunar SDA constellation design and analysis framework that integrates state …

Venus Balloon Localization: A Map-Aided Navigation Approach Supported By A Single-Satellite, Heath Scott Cottrill

Graduate Theses, Dissertations, and Problem Reports (ETD)

Although Venus and Earth began as twins, possessing comparable size, mass, and composition, past exploration missions have revealed that Venus is now hellishly hot, devoid of oceans, and enveloped in a carbon dioxide-filled atmosphere. To understand when and why this evolutionary divergence occurred, further exploration is required. Today, there is a growing interest in the use of aerial platforms to circumvent the harsh conditions at the surface, which limit the lifetime of landed instruments. In this concept, a single balloon, propelled by the ambient wind field, would operate in the atmosphere at an altitude between 50 and 70 km, where …

Leveraging Artificial Intelligence To Improve Data Configuration & Accuracy In Modern Flight Management Systems, Sreeram Chittayil

International Journal of Aviation, Aeronautics, and Aerospace

AI (Artificial intelligence) can automate the process of generating optimized flight routes using real-time data, such as AIRAC (Aeronautical Information Regulation and Control), significantly reducing the time needed for flight management tasks. While AIRAC data typically takes up to 28 days to refresh, AI could condense this process to just minutes, enhancing operational efficiency and ensuring pilots have timely and accurate flight information. The research includes practical experiments, prototype code, and visual case studies to demonstrate AI's role in optimizing FMS functions while addressing issues related to data input errors and human intervention. Key findings from trials show the algorithm's …

External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow

Theses and Dissertations

In the past two decades, Unmanned Aerial Systems have progressed from expensive military hardware or one-off custom builds, to include off-the-shelf drones that can be purchased for a rather affordable price and flown by nearly anyone. As the technology and performance have improved, the door is opened to applications that require operation in environments where the consequences for failure are high, such as operating in the navigable airspace or in urban environments, or with human passengers. This requires a great deal of trust in the reliability and integrity of the control systems of the aircraft. A method of monitoring the …

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …

Artificial Intelligence-Assisted Inertial Geomagnetic Passive Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

In recent years, the integration of machine learning techniques into navigation systems has garnered significant interest due to their potential to improve estimation accuracy and system robustness. This doctoral dissertation investigates the use of Deep Learning combined with a Rao-Blackwellized Particle Filter for enhancing geomagnetic navigation in airborne simulated missions.

A simulation framework is developed to facilitate the evaluation of the proposed navigation system. This framework includes a detailed aircraft model, a mathematical representation of the Earth's magnetic field, and the incorporation of real-world magnetic field data obtained from online databases. The setup allows an accurate assessment of the performance …

Verification And Validation Of Robot Manipulator Adaptive Control With Actuator Deficiency, Sebastian Comeaux

Doctoral Dissertations and Master's Theses

This work addresses the joint tracking problem of robotic manipulators with uncertain dynamical parameters and actuator deficiencies, in the form of an uncertain control effectiveness matrix, through adaptive control design, simulation, and experimentation. Specifically, two novel adaptive controller formulations are implemented and tested via simulation and experimentation. The proposed adaptive control formulations are designed to compensate for uncertainties in the dynamical system parameters as well as uncertainties in the control effectiveness matrix that pre-multiplies the control input. The uncertainty compensation of the dynamical parameters is achieved via the use of the desired model compensation–based adaptation, while the uncertainties related to …

Deep-Learning Based Multiple-Model Bayesian Architecture For Spacecraft Fault Estimation, Rocio Jado Puente

Doctoral Dissertations and Master's Theses

This thesis presents recent findings regarding the performance of an intelligent architecture designed for spacecraft fault estimation. The approach incorporates a collection of systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.

To assess the effectiveness of this architecture, a range of performance metrics is employed. Through extensive numerical simulations and in-lab experimental testing utilizing a dedicated spacecraft testbed, the capabilities and accuracy of the proposed intelligent architecture are analyzed. These evaluations provide valuable insights into the architecture's ability to detect and classify …

Development Of A Constellation Simulator For A 5g/Iot Mission Planning System, Franco Criscola

Doctoral Dissertations and Master's Theses

The advancement of 5G and Internet-of-Things technologies has presented new challenges for telecommunications providers. One of the challenges is integrating these technologies with present networks. A solution has been found in low-Earth orbit satellite constellations. On one hand, this method increases coverage and reduces costs, but on the other it raises new problems like how to efficiently manage large constellations of spacecraft. This thesis introduces the Constellation Management System, developed in collaboration with i2Cat foundation. This novel tool is composed of two modules: the simulator and the scheduler. The former propagates satellite motion and computes visibility events to various targets …