Computer Engineering Commons^™

Predictive Ai Applications For Sar Cases In The Us Coast Guard, Joshua Nelson

Cybersecurity Undergraduate Research Showcase

This paper explores the potential integration of predictive analytics AI into the United States Coast Guard's (USCG) Search and Rescue Optimal Planning System (SAROPS) for deep sea and nearshore search and rescue (SAR) operations. It begins by elucidating the concept of predictive analytics AI and its relevance in military applications, particularly in enhancing SAR procedures. The current state of SAROPS and its challenges, including complexity and accuracy issues, are outlined. By integrating predictive analytics AI into SAROPS, the paper argues for streamlined operations, reduced training burdens, and improved accuracy in locating drowning personnel. Drawing on insights from military AI applications …

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 …

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 …

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.

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan

Symposium of Student Scholars

"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …

A New Algorithm For Encounter Generation: Encounters From Actual Trajectories (Enact), James Anthony Ritchie Iii

Theses and Dissertations

There is ongoing research at the Federal Aviation Administration (FAA) and other private industries to examine a concept for delegated separation in multiple classes of airspace to allow unmanned aircraft systems (UAS) to remain well clear of other aircraft. Detect and Avoid (DAA) capabilities are one potential technology being examined to maintain separation. To evaluate these DAA capabilities, input traffic scenarios are needed, but current approaches are limited by the breadth of the traffic recordings available. This thesis derives a new mathematical algorithm that uses great circle navigation equations in an Earth spherical model and an accurate aircraft performance model …

Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

Machine learning regression techniques have shown success at feedback control to perform near-optimal pinpoint landings for low fidelity formulations (e.g. 3 degree-of-freedom). Trajectories from these low-fidelity landing formulations have been used in imitation learning techniques to train deep neural network policies to replicate these optimal landings in closed loop. This study details the development of a near-optimal, neural network feedback controller for a 6 degree-of-freedom pinpoint landing system. To model disturbances, the problem is cast as either a multi-phase optimal control problem or a triple single-phase optimal control problem to generate examples of optimal control through the presence of disturbances. …

Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …

A Study Of 5g Cellular Connectivity To Unmanned Aerial Vehicles, Jackson Murrin

All Theses

The market of unmanned aerial vehicles (UAVs) has seen significant growth in the past ten years on both the commercial and military sides. The applications for UAVs are endless and options by manufacturers allow users to modify their drones for their specific goals. This industry has opened up the excitement of piloting vehicles in the air, photography, videography, exploration of nature from a different point of view and many other hobbies assisted by the emergence of UAVs. The growth of this industry coincides with the roll out of new 5G cellular network technology. This upgrade in cellular network infrastructure allows …

Data-Driven Predictive Modeling To Enhance Search Efficiency Of Glowworm-Inspired Robotic Swarms In Multiple Emission Source Localization Tasks, Payal Nandi

Mechanical & Aerospace Engineering Theses & Dissertations

In time-sensitive search and rescue applications, a team of multiple mobile robots broadens the scope of operational capabilities. Scaling multi-robot systems (< 10 agents) to larger robot teams (10 – 100 agents) using centralized coordination schemes becomes computationally intractable during runtime. One solution to this problem is inspired by swarm intelligence principles found in nature, offering the benefits of decentralized control, fault tolerance to individual failures, and self-organizing adaptability. Glowworm swarm optimization (GSO) is unique among swarm-based algorithms as it simultaneously focuses on searching for multiple targets. This thesis presents GPR-GSO—a modification to the GSO algorithm that incorporates Gaussian Process Regression (GPR) based data-driven predictive modeling—to improve the search efficiency of robotic swarms in multiple emission source localization tasks. The problem formulation and methods are presented, followed by numerical simulations to illustrate the working of the algorithm. Results from a comparative analysis show that the GPR-GSO algorithm exceeds the performance of the benchmark GSO algorithm on evaluation metrics of swarm size, search completion time, and travel distance.

Sensor Module Network For Monitoring Trace Gases In The International Space Station, Aaron Beck, Drake Provost, Christopher English, Kamrin Gustave

Honors Capstones

The Jet Propulsion Laboratory (JPL) of the National Aeronautics and Space Administration (NASA) aims to develop a sensor network for the International Space Station (ISS) to ensure a comprehensive understanding of air quality within the station. The accumulation of carbon dioxide (CO­­­­­₂) can lead to cognitive impairment, headaches, and potentially dangerous situations at high concentrations. Monitoring air content at the ISS is critical to maintaining a healthy environment for crew onboard. Exposure to harmful gases causes negative side effects that make crew sick, which may interfere with their responsibilities. CO₂ is a gas that should be monitored …

Accurate Indoor Navigation System Based On Imu/Lp-Mm Integrated Method Using Kalman Filter Algorithm, Abdullah Mohammed Bahasan

Hadhramout University Journal of Natural & Applied Sciences

Abstract

The demand for navigation systems is rapidly increasing, especially in indoor environments which the signal of GPS is not available. Therefore the Inertial Measurement Unit (IMU) system is a suitable navigation system in such indoor environments. It usually consists of three accelerometers and three gyroscopes to determine position, velocity and attitude information, respectively, without need of any external source. But this type of navigation systems has errors growth with time due to accelerometers and gyroscopes drifts. This paper introduces indoor navigation system based on integrated IMU navigation system with proposed system called Landmarks Points-Map Matching (LP-MM) system using Kalman …

Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo

Student Works

Aircraft taxiing operations in the aerodrome were identified to consume the most jet fuel apart from the cruise phase of the flight. This was also well supported by various research associating taxi operations at large, congested airports, with high jet fuel consumption, high carbon emissions, and noise pollution. Existing literature recognised the potential to address the environmental issues of aerodrome taxi operations by operating External or Onboard Aircraft Ground Propulsion Systems (AGPS). Designed to power aircraft with sources other than their main engines, external Aircraft Ground Power Systems (AGPS) have shown the potential to significantly cut jet fuel consumption and …

Ads-B Communication Interference In Air Traffic Management, George Ray

International Journal of Aviation, Aeronautics, and Aerospace

Automated Dependent Surveillance Broadcast (ADS-B) provides position and state information about aircraft and is becoming an essential component in the global air traffic management system. ADS-B transponders broadcast this key information on a common frequency to both other aircraft and to secondary surveillance radar systems located at ground stations. Both the aircraft transponders and the ground stations work together to assist in managing the commercial airspace. Since the aircraft transponders all broadcast on the same frequency and are in close proximity there is an apparent risk of interference and the garbling of the communications needed to manage the airspace.

The …

Space Force Design Project, Emily Greene, Ashton Orosa, Julia Patek, Nathan Doty

Williams Honors College, Honors Research Projects

The objective of our research project is to develop a lab testbed composed of a curved surface to represent a spacecraft hull, a mobile robot equipped with repair tools, and a robotic arm equipped with a laser 3D scanner. This project is part of a larger grant to the University of Akron from Space Force and Air Research Labs. The lab testbed developed in this project will be used to assist in creating and testing a software and algorithm to inspect and repair spacecraft while in orbit. The project will involve researching spacecraft hulls to create an accurate simulation bed, …

Media Streaming In A High-Rate Delay Tolerant Network, Kyle Vernyi

Williams Honors College, Honors Research Projects

Audio and video streaming across delay tolerant networks are relatively new phenomena. During the Apollo 11 mission, video and audio were streamed directly back to Earth using fully analog radios. This streaming capability atrophied over time. The gradual conversion to digital electronics contributed greatly to this. Additionally, 21st century space systems face the new requirement of interconnectedness. Delay Tolerant Networking (DTN) attempts to solve this requirement by uniting traditional point to point links into a robust and dynamic network. However, DTN implementations present bottlenecks due to low performance. High-Rate Delay Tolerant Networking (HDTN) is a performance-optimized DTN implementation. This work …

Motion Planning In Artificial And Natural Vector Fields, Bernardo Martinez Rocamora Junior

Graduate Theses, Dissertations, and Problem Reports

This dissertation advances the field of autonomous vehicle motion planning in various challenging environments, ranging from flows and planetary atmospheres to cluttered real-world scenarios. By addressing the challenge of navigating environmental flows, this work introduces the Flow-Aware Fast Marching Tree algorithm (FlowFMT*). This algorithm optimizes motion planning for unmanned vehicles, such as UAVs and AUVs, navigating in tridimensional static flows. By considering reachability constraints caused by vehicle and flow dynamics, flow-aware neighborhood sets are found and used to reduce the number of calls to the cost function. The method computes feasible and optimal trajectories from start to goal in challenging …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Energy Dissipation In A Sand Damper Under Cyclic Loading, Ehab Sabi

Civil and Environmental Engineering Theses and Dissertations

Various seismic and wind engineering designs and retrofit strategies have been in development to meet structures' proper and safe operation during earthquake and wind excitation. One such method is the addition of fluid and particle dampers, such as sand dampers, in an effort to reduce excessive and dangerous displacements of structures. The present study implements the discrete element method (DEM) to assess the performance of a pressurized sand damper (PSD) and characterize the dissipated energy under cyclic loading. The idea of a PSD is to exploit the increase in shearing resistance of sand under external pressure and the associated ability …

Certification Basis For A Fully Autonomous Uncrewed Passenger Carrying Urban Air Mobility Aircraft, Steve Price

Student Works

The Urban Air Mobility campaign has set a goal to efficiently transport passengers and cargo in urban areas of operation with autonomous aircraft. This concept of operations will require aircraft to utilize technology that currently does not have clear regulatory requirements. This report contains a comprehensive analysis and creation of a certification basis for a fully autonomous uncrewed passenger carrying rotorcraft for use in Urban Air Mobility certified under Title 14 Code of Federal Regulations Part 27. Part 27 was first analyzed to determine the applicability of current regulations. The fully electric propulsion system and fully autonomous flight control system …

Actively Guided Cansats For Assisting Localization And Mapping In Unstructured And Unknown Environments, Cary Chun, M. Hassan Tanveer

Symposium of Student Scholars

When navigating in unknown and unstructured environments, Unmanned Arial Vehicles (UAVs) can struggle when attempting to preform Simultaneous Localization and Mapping (SLAM) operations. Particularly challenging circumstance arise when an UAV may need to land or otherwise navigate through treacherous environments. As the primary UAV may be too large and unwieldly to safely investigate in these types of situations, this research effort proposes the use of actively guided CanSats for assisting in localization and mapping of unstructured environments. A complex UAV could carry multiple of these SLAM capable CanSats, and when additional mapping and localization capabilities where required, the CanSat would …

Unmanned Aerial System Design For Civil Engineering Operations – A Vip Study, Ezra Robles, Harrison Vicknair, Derek Price, Logan Westra, George Pitcock, Joshua Diamond, Bhuvan Saraswat, Jeremiah Prayor, Fon Saliki

Symposium of Student Scholars

Unmanned Aerial System Design for Civil Engineering Operations – A Case Study

The objective of the project is to design and build a modular Unmanned Aerial System (UAS) that meets the specifications set forth by United Consulting – a local civil engineering company. These specifications are achieved through three unique missions. In each mission, data is collected using different methods. These missions include land surveying, bridge structure inspection and manhole probing. The key requirements of the drone are to maintain a minimum flight time of 30 minutes and the ability to receive and transmit telemetry, photographic and video data from …

Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng

All Dissertations

Multi-robot systems (MRS) can accomplish more complex tasks with two or more robots and have produced a broad set of applications. The presence of a human operator in an MRS can guarantee the safety of the task performing, but the human operators can be subject to heavier stress and cognitive workload in collaboration with the MRS than the single robot. It is significant for the MRS to have the provable correct task and motion planning solution for a complex task. That can reduce the human workload during supervising the task and improve the reliability of human-MRS collaboration. This dissertation relies …

Low-Cost Uav Swarm For Real-Time Object Detection Applications, Joel Valdovinos Miranda

Master's Theses

With unmanned aerial vehicles (UAVs), also known as drones, becoming readily available and affordable, applications for these devices have grown immensely. One type of application is the use of drones to fly over large areas and detect desired entities. For example, a swarm of drones could detect marine creatures near the surface of the ocean and provide users the location and type of animal found. However, even with the reduction in cost of drone technology, such applications result costly due to the use of custom hardware with built-in advanced capabilities. Therefore, the focus of this thesis is to compile an …

Early Warning Reentry System Comprising High Efficiency Module For Determining Spacecraft Reentry Time, Robert A. Bettinger

AFIT Patents

The present invention relates to an early warning reentry system comprising a high efficiency module for determining spacecraft reentry time and a highly efficient method for determining spacecraft reentry time. The method permits more accurate, earlier spacecraft reentry time determinations using publicly available trajectory information without the need for accounting for the actual design configuration of the spacecraft in question. Thus, a module for making such determinations can easily and inexpensively be added to an early warning reentry system.

Characterizing And Predicting Human Visual Perception Of Unmanned Aerial Vehicle Gestures, Paul Fletcher

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Unmanned Aerial Vehicles (UAVs) are being used in public domains and hazardous environments where effective communication strategies are critical. UAV gesture techniques have been shown to communicate meaning to human observers and may be ideal in contexts that require lightweight systems such as unmanned aerial flight, however, this work may be limited to an idealized range of viewer perspectives. As gesture is a visual communication technique it is necessary to consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This thesis presents the results of three online user-studies that examine participants’ ability …

Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi

Frameless

Circle Optics is developing novel technology for low-parallax, real time, panoramic image capture using an integrated array of multiple adjacent polygonal-edged cameras. This technology can be optimized and deployed for a variety of markets, including cinematic VR. Circle Optics’ existing prototype, Hydra Alpha, will be demonstrated.

A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert

Student Research

Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …