Navigation, Guidance, Control and Dynamics Commons^™

Using Convolutional Neural Networks For Autonomous Drone Navigation, Joshua Jowers

Industrial Engineering Undergraduate Honors Theses

Unmanned Aerial Vehicles (UAVs), more commonly known as drones, serve various purposes, notably in military applications. Consequently, there arises a need for navigation methods impervious to intercepted signals [1]. Previous research has explored numerous solutions, including machine learning. This paper delves into a specific machine learning approach employing a Convolutional Neural Network (CNN) to discern image locations [2]. It elucidates the conversion of a CNN model between two machine learning libraries and presents results from multiple experiments examining parameters and factors influencing the approach's efficacy. These experiments encompass testing different data sources, image quantities, and processing pipelines to gauge their …

Design And Implementation Of A Launching Method For Free To Oscillate Dynamic Stability Testing, Kristen M. Carey

Mechanical & Aerospace Engineering Theses & Dissertations

Magnetic Suspension and Balance Systems (MSBS) allow for static, forced oscillation and free to oscillate dynamic stability testing in a wind tunnel without the need for a physical support. The objectives of study are to assist in the application of the free to oscillate testing method in an MSBS to determine dynamic stability characteristics for various re-entry capsule designs.

This thesis discusses the development and testing of a launching method called the grabber for use in the MSBS Subsonic Wind Tunnel at NASA Langley Research Center. Aerodynamic tests were run to support the use of this method and compare the …

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Space Dynamics Laboratory Payload Challenge: Autonomous Water Sampling Uav, Thomas Wheeler, Zachary Williams, Joseph Stack

Williams Honors College, Honors Research Projects

The following report has been completed over the course of the Fall 2018 and Spring 2019 semesters at The University of Akron by Joseph P. Stack (Aerospace Systems Engineering), Thomas J. Wheeler (Mechanical Engineering) and Zachary M. Williams (Mechanical Engineering). The purpose of this project was to create a payload system for the Akronauts Rocket Design Team to use at the Intercollegiate Rocket Engineering Competition (IREC) Spaceport America Cup. The Competition as a challenge that is sponsored by Space Dynamics Laboratory specifically regarding payload systems. The challenge in very open-ended and allows student to identify their own scientific experiment and …

Analysis Of Online-Delaunay Navigation For Time Sensitive Targeting, David Chow

Theses and Dissertations

Given the drawbacks of leaving time-sensitive targeting (TST) strictly to humans, there is value to the investigation of alternative approaches to TST operations that employ autonomous systems. This paper accomplishes five things. First, it proposes a short-hop abbreviated routing paradigm (SHARP) - based on Delaunay triangulations (DT), ad-hoc communication, and autonomous control - for recognizing and engaging TSTs that, in theory, will improve upon persistence, the volume of influence, autonomy, range, and situational awareness. Second, it analyzes the minimum timeframe need by a strike (weapons enabled) aircraft to navigate to the location of a TST under SHARP. Third, it shows …