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 …

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 …

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 …

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.

Theory And Algorithms To Learn, Propagate, And Exploit Uncertainty For Stochastic Optimal Control Of Dynamical Systems, Vignesh Sivaramakrishnan

Electrical and Computer Engineering ETDs

Non-Gaussian uncertainty frequently arises in learning and control problems involving stochastic dynamical systems, particularly in autonomous vehicles, UAVs, satellites, and robotics. In this dissertation, we propose a new framework that leverages characteristic functions that provides a frequency-domain representation of random variables. The dissertation is structured into three key areas. First, we address model-based stochastic optimal control for linear systems with non-Gaussian noise, demonstrating that characteristic functions can be used to enforce chance constraints and control systems toward desired distributions. Second, we explore data-driven stochastic control, utilizing empirical characteristic functions to handle systems with unknown disturbances. In addition, we derive several …

Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor

Faculty Publications

This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …

An Investigation Into The Use Of Amateur Astronomy Equipment For Optical Orbit Determination Using A Mobile Telescope Platform, Johan C. Govaars

Master's Theses

The process of optical orbit determination has long been in the domain of large organizations and stationary observatories with highly specialized scientific equipment. This thesis seeks to determine not only if satellites can be captured regularly using purely commercial-off-the-shelf (COTS) equipment, but also if initial orbit determinations can be made using that data. Moreover, the use of a mobile telescope platform allows users to circumvent the restrictions of fixed observatories such as low horizon viewing restrictions or existing light pollution.

A completely COTS setup was utilized that included an 8-inch Celestron NextStar 8SE telescope with an f/6.3 focal reducer and …

Learning-Based Feature Identification For Rendezvous And Capture Of Non-Cooperative Space Objects, Trupti Mahendrakar

Theses and Dissertations

In recent years, On-Orbit Servicing (OOS) and Active Debris Removal (ADR) have attracted increasing interest due to growing concerns about space debris. This debris poses a significant risk to spacecraft, as collisions can catastrophically end missions and potentially trigger a cascading chain reaction of more debris. Space debris ranges from tiny paint chips to large non-functional spacecraft and even launch vehicle components. One way to mitigate the formation of additional space debris is to reduce the total number of large non-cooperative resident space objects present in operational orbits. This can be achieved through two approaches: de-orbiting these objects as part …

Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins

Theses and Dissertations

This dissertation advances the development of robust learning-based approaches across two complementary domains: engineering education and autonomous systems. Through four studies, this research addresses critical challenges in preparing data-proficient engineers and developing reliable autonomous systems that can operate under uncertainty and incomplete information. The engineering education study examines how mechanical and aerospace engineering undergraduates conceptualize and develop data proficiency skills essential for modern engineering practice. Through interviews with 27 students, the research employs the How People Learn framework to analyze student perspectives on information literacy, data interpretation, and computational thinking. The findings inform pedagogical strategies for developing data proficiency in …

Organisational Resilience : A Study Of The Resilience Of Maritime Stakeholders In Ghana, Priscilla Ami Dogbeda Dzokoto

World Maritime University Dissertations

No abstract provided.

Stereo Vision Relative Navigation Of Airborne Vehicles, Scott L. Nykl, Brian Woolley, John Pecarina

AFIT Patents

An automated aerial formation (AAF) system includes an imaging device mounted on an imaging first aircraft that receives reflected energy from an imaged second aircraft. A controller is communicatively coupled to the imaging device and a flight control system of one of the first and the second aircraft. The controller generates a three-dimensional (3D) point cloud based on the reflected energy and identifies a target 3D model in the 3D point cloud. The controller rotates and scales one of a pre-defined 3D model and the target 3D model to find a 3D point registration between the target 3D model and …

Spacecraft Attitude Control Simulator, Bricen S. Rigby

College of Engineering Summer Undergraduate Research Program

The Spacecraft Attitude Control Simulator is a single-axis attitude control platform which is intended to recreate the frictionless space environment in order to test cold-gas thruster control schemes. The overall goal of this research project was to observe settling data from the platform and compare it to simulated data. In practice, the predicted settling time was only 7% larger than observed settling time.

Development Of Python Library For Spacecraft Modeling, Shreya Kale

College of Engineering Summer Undergraduate Research Program

This project involved developing a python library to be used in modeling spacecraft attitude dynamics and control

Attitude Control Of A Flexible Flapping Wing Uav Based On Fuzzy Logic, Reed M. Paulson, Tyson Chen, Diego Del Real, Nico Morrison

College of Engineering Summer Undergraduate Research Program

This project revolves around creating an a attitude controller for a hovering flexible flapping wing UAV that is based on a flying hummingbird. We based our model from a paper by Banazadeh and Taymourtash1 , First replicating the open-loop results using the nonlinear dynamic model and the equations of motion (seen below) while considering aerodynamic loads. Once replicated, we then used fuzzy logic to model the dynamic model. Subsequently, we designed a fuzzy controller to stabilize the hovering mode. We then considered and detailed future work needed to make further progress in this area.

Model Predictive Control For Autonomous Landing In Complex Scenarios, Konstantinos Sotirakos

Doctoral Dissertations and Master's Theses

The autonomous flight industry is ever-expanding and continuing to push the boundaries of what is possible within the limitations of technology. Multiple companies are exploring the use of autonomous flight for intra-city travel with air taxi services and package delivery vehicles. Other companies are exploring the use of autonomous vehicles for military applications, such as Sikorsky with a next generation Black Hawk helicopter to ensure the safety of soldiers in high threat or altogether dangerous scenarios. In this thesis model predictive control (MPC) algorithms are developed to enable a quadcopter to operate and land autonomously in challenging environments. Specifically, MPC …

Adaptive Control And Estimation Of The Center Of Mass Of A 5-Degree-Of-Freedom Spacecraft Testbed, Pol Fontdegloria Balaguer

Doctoral Dissertations and Master's Theses

In space applications, on-ground experimentation is an essential step in control algorithm validation before real mission application. However, on-ground conditions greatly differ from space ones, where satellites operate under extremely low gravity and friction conditions. A common way to simulate these conditions is with air-bearing-based testbeds. These testbeds reduce friction significantly to almost space-like conditions. Air-bearing technology can provide virtually frictionless translational and rotational motion. However, when frictionless rotational motion is achieved, the testbed becomes highly sensible gravity torque. This external torque is produced by the offset between the predetermined geometrical center of rotation (CoR) and the center …

Computer Based Modeling For Small E-Vtol Propeller Performance, Ege Konuk

Mechanical & Aerospace Engineering Theses & Dissertations

The emerging field of urban air mobility (UAM) offers a novel transportation method for civil, commercial, and military applications. Vertical take-off and landing (VTOL) configurations present challenges for performance prediction during crucial flight operations. An advanced computational framework for predicting propeller performance in electric vertical takeoff and landing (eVTOL) aircraft during transition flight is essential for future concept designs. This research extends the Blade Element Momentum Theory (BEMT) to model propeller behavior at high incidence angles, crucial for eVTOL operation.

The study begins with a review of tilt-wing/rotor configurations for eVTOLs and tackles the complex aerodynamic phenomena associated with rotors …

Koopman-Based Modeling For Nonlinear Control Of Multirotor Uavs, Simone Martini

Electronic Theses and Dissertations

This PhD dissertation focuses on adopting the emerging Koopman Operator theory for modeling and nonlinear control of multirotor UAVs, focusing specifically on quadrotors for proof-of-concept demonstration purposes.

The Koopman Operator theory is based on the foundation that nonlinear dynamics in the state space may be represented as a linear evolution of some functions in the state space. Thus, using appropriately defined and possibly nonlinear functions of the state variables, called observables, as a new and maybe infinite set of coordinates that are referred to as lifted space, the original nonlinear dynamics appear to be linear. The implications of this theory …

Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen

Faculty Publications

Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method continues to be the industry standard and was developed when airborne magnetic survey aircraft were first employed over 70 years ago. In this paper, we present a magnetic calibration algorithm based on a factor graph optimization using inertial measurements as well as inputs from both a vector and scalar magnetometer. …