Computer Engineering Commons^™

A Comparative Classical And Data-Driven Facial Analysis Of Wide-Field-Of-View Lens Captures, Andrew Murphy, Giovanni C. Decapua, Anthony M. Cafiso, Max E. Raabe, Kaden E. Van Leuven

Discovery Day - Daytona Beach

WFOV lenses are becoming popular in facial recognition due to the fact that they enhance subject coverage and improve the chances of detecting target faces. However, wide-angle optics introduce nonlinear distortion around the image periphery, which degrades the performance of recognition pipelines. In this poster presentation, we use WFOV lens captures to analyze facial recognition using classical low-complexity algorithms based on the discrete Fourier transform (DFT), discrete cosine transform (DCT), principal component analysis (PCA), and data-driven learning with convolutional neural networks. Finally, we present computational efficiency, compression, accuracy, and precision of recognizing distorted images with qualitative and quantitative measures.

Hydroquad - A Drone Quadruped Hybrid, Haitish Gandhi, Dheer Chhabria

Discovery Day - Daytona Beach

The HyDroQuad is a hybrid robotic system designed to navigate environments where traditional robots face limitations. By combining a quadrupedal walking mechanism with an aerial drone, the platform is able to walk efficiently on stable terrain and transition to flight when encountering obstacles such as rocks, gaps, or steep slopes. This adaptability makes it a strong candidate for future planetary exploration, where terrain is often uneven and unpredictable. This work focuses on developing and evaluating a functional prototype of the system. A fully integrated platform, HDQ-MK1, was designed and constructed by combining a lightweight multirotor drone with a compact quadruped …

A Cyber-Physical Flight Simulation Platform For Real-Time Visualization Of Aircraft Dynamics And Sensor-Based Control, Gabriel Martinez, Michael Poinsett

Discovery Day - Daytona Beach

Understanding aircraft dynamics through traditional simulations can be limiting, as results are often confined to screen-based visualization. This project aims to enhance learning and experimentation by creating a system where aircraft motion can be both simulated and physically observed in real time. The primary objective is to develop a cyber-physical flight simulation platform that links mathematical models with physical hardware. The system is designed to (1) represent aircraft dynamic behavior through real-time motion and (2) provide a foundation for integrating sensors and control strategies for responsive flight behavior. The platform combines aircraft dynamic models with a hardware interface capable of …

Radaround: A Field-Expedient Direction Finder For Contested Iot Sensing & Em Situational Awareness, Owen Maute, Blake Roberts

Discovery Day - Daytona Beach

This paper presents RadAround, a passive 2-D direction-finding system designed for adversarial IoT sensing in contested environments. Using mechanically steered narrowbeam antennas and field-deployable SCADA software, it generates high-resolution electromagnetic (EM) heatmaps using low-cost COTS or 3D-printed components. The microcontroller-deployable SCADA coordinates antenna positioning and SDR sampling in real time for resilient, on-site operation. Its modular design enables rapid adaptation for applications such as EMC testing in disaster-response deployments, battlefield spectrum monitoring, electronic intrusion detection, and tactical EM situational awareness (EMSA). Experiments show RadAround detecting computing machinery through walls, assessing utilization, and pinpointing EM interference (EMI) leakage sources from Faraday …

Improving Multi-Agent Swarm Collision Avoidance Using Reciprocal Velocity Obstacles, Nick Wilson

Discovery Day - Daytona Beach

As multi-agent systems grow increasingly complex, physical robotic swarms are essential to bridge the gap between limited software simulations and real-world application. The BID4R STARS swarm provides a physical platform for testing diverse algorithms, yet its success relies heavily on fundamental agent capabilities—most notably, obstacle avoidance. Preventing intra-swarm collisions is critical to avoid hardware damage and experimental disruption. To address this challenge, this project implements the Reciprocal Velocity Obstacles (RVO) algorithm onto the STARS swarm. While standard collision avoidance algorithms often overcorrect and induce oscillatory agent movement, RVO factors in the velocity and anticipated responses of all agents involved in …

Honeybee-Inspired Swarm Intelligence For Autonomous Adaptability Of Martian Infrastructure, Morgan Kendall

Discovery Day - Daytona Beach

Current research in autonomous space systems primarily relies on centralized control or swarm methods designed for fixed mission scenarios. These approaches lack the flexibility needed for long-duration Mars operations, where infrastructure must adapt to changing conditions, evolving mission goals, and limited human oversight. This creates a critical gap in developing autonomous systems capable of continuous self-organization. This gap is being addressed by developing a biologically inspired, adaptive Martian infrastructure using swarm intelligence. The scope includes key system domains such as power distribution, communication networks, and surface logistics. Agent-based modeling software will simulate infrastructure components as autonomous agents that evaluate local …

Nano Aircraft Using Underactuated Technology (Naut), Giol Vinyals I Roca

Discovery Day - Daytona Beach

The Nano Aircraft using Underactuated Technology (NAUT) project presents a novel swashplateless rotor system that achieves cyclic pitch control using a single actuator, eliminating the need for conventional multi-servo swashplate assemblies. This approach is specifically tailored for nano unmanned aircraft systems (UAS) operating within Advanced Air Mobility (AAM) environments, where size, weight, and power constraints demand highly efficient and simplified control architectures. A functional prototype has been developed and experimentally validated, demonstrating measurable cyclic pitch variation and effective control authority. Multiple mechanism variants are currently being investigated to evaluate performance trade-offs in responsiveness, mechanical efficiency, and aerodynamic effectiveness. These configurations …

Remora Ads-B In Receiver, Noah Evans, Sara Patel, Nicholas Gatto, Daniel Ingleton

Discovery Day - Daytona Beach

The Remora is a compact Automatic Dependent Surveillance Broadcast (ADS-B) receiver, designed to enhance situational awareness for pilots operating experimental and homebuilt aircraft. Unlike conventional panel or windscreen-mounted systems, the Remora is installed externally, making it a low-profile solution to the ADS-B In challenge. The device integrates easily with the aircraft’s existing power supply. It transmits data wirelessly to electronic flight bags (EFBs) within the cockpit, using existing iOS and Android software for display and user interaction.   The primary function of the Remora is to provide public-access, real-time traffic awareness and weather forecasting, enabling pilots to make informed mission decisions. …

Orbital Servicing Calibration And Repair (O.S.C.A.R.), Samantha Rogers, Chloe Arnold, Ava Laudadio

Discovery Day - Daytona Beach

Low Earth Orbit (LEO) satellites operate in an environment that exposes them to cumulative radiation effects, micrometeoroids, and orbital debris, and limited opportunities for post-launch intervention. These factors can degrade satellite performance over time, leading to anomalies that may cause data corruption, mission failure, or require human intervention for repair. While previous on-orbit servicing efforts have demonstrated repair and life-extension capabilities, most have focused on Geosynchronous satellites or controlled test environments, leaving a gap in servicing concepts tailored specifically to LEO satellites.The O.S.C.A.R. (Orbital Servicing, Calibration, and Repair) project investigates the design of a robotic servicing system for inspecting, calibrating, …

Designing Under Pressure: A Comparative Study Of Ai And Manual Interface Development In A Naval Weapon System Scenario, Tsimur Babakhanau, Noah Clark, Colby Keller, Mary Grace Sorenson, Zoe Tiede

Discovery Day - Daytona Beach

This study implements a detailed naval scenario in which participants acted as operators on a Navy destroyer equipped with a Laser Weapon System (LaWS). Their task was to create a dashboard capable of stopping incoming suicide drone swarms while managing critical laser functions such as thermal constraints, threat prioritization, and adapting to attack dynamics. Poor management could leave the ship vulnerable. AI is increasingly integrated into design methods, fundamentally transforming the process of building user interfaces by compressing hours of work into minutes. Although AI design tools are becoming more common, little is known about how well beginners can use …

Navigating Enhanced Exploration Assistance (Nexa), Azhari Abbas, Caleb Fakunle, Ryan Powell, Donovan Livingston

Discovery Day - Daytona Beach

NEXA is an artificial intelligence software platform developed to enhance residential security and property monitoring through seamless integration with autonomous drone systems. This research application of advanced AI in surveillance aims to create a standalone solution capable of real-time threat detection and intelligent alert management. By processing visual and sensory data, NEXA facilitates autonomous drone operation with minimal human intervention. Secure communication channels ensure that instant alerts are delivered to property owners and, potentially, law enforcement, improving response times in security incidents, search-and-rescue operations, and perimeter surveillance. Additionally, NEXA is capable of interfacing with commercially available drone platforms and presents …

Robotic Arm Development For Cone Penetration Testing On The Lunar Surface, Jonah Graff, Derek Zhang

Discovery Day - Daytona Beach

Just as on Earth, future lunar operations will require accurate characterization of surface conditions. On Earth, a proven method for this is Cone Penetration Testing (CPT), which evaluates soil bearing capacity and stratification. This information is vital for lunar operations, including habitat construction, resource extraction, and safe pathfinding. However, traditional CPT systems are designed for human operation and lack autonomy. This project addresses that limitation by developing an autonomous, in-situ terrain characterization system for lunar surfaces. The device is driven by ball-screw actuators powered by stepper motors and controlled through an Arduino Mega, using a combination of metal and 3D-printed …

Advanced Manufacturing And Materials Of A Bio-Mimetic Hoof For Space Robotics Applications, Benjamin Heckel

Discovery Day - Daytona Beach

Planetary surfaces often feature steep, uneven, and unpredictable terrain conditions that resemble some of the most challenging natural environments on Earth. In these terrestrial settings, certain animals have evolved to navigate complex landscapes with remarkable agility. One example is the mountain goat, an animal whose hooves have evolved for stable and precise movement across rocky, inclined surfaces. This biological adaptation provides a useful model for improving robotic mobility in planetary exploration. This study draws inspiration from that natural adaptation to develop a bio-mimetic robotic hoof designed to enhance traction, durability, and adaptability for extraterrestrial exploration. By replicating the mechanical properties …

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods

Discovery Day - Daytona Beach

Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …

Interplay Between Physical Design Choices And Emergent Cyber System Consensus: A Case Study With An Underwater Swarm, Ava Neubert

Discovery Day - Daytona Beach

Understanding how physical constraints influence collective behavior is critical for designing cyber-physical multi-agent systems in communication-limited environments. This project investigates how agent mobility and communication constraints affect opinion dynamics in a three-dimensional underwater swarm. An agent-based model was developed in AnyLogic, where agents follow realistic motion dynamics and exchange information at discrete communication intervals to reflect underwater limitations. Agent opinions are modeled using a BOIDS-inspired consensus mechanism in RGB space, allowing visualization of convergence behavior. A sensitivity analysis was conducted to evaluate the effects of communication range, agent speed, turn rate, and swarm size. Results show that communication range has …

Automation And Robotics In Timber Construction Prefabrication, Jason Grabowski, Anish Mandyam, Samuel Mcaraw, Jacob Jander

Discovery Day - Daytona Beach

Robotics and automation have varying degrees of utilization across the construction prefabrication industry. The timber prefabrication industry is uniquely positioned for the implementation of robotics and automation due to the environment being more controlled than most of the construction industry. Current developments are influenced by the evolution of "Construction 4.0/5.0," where the integration of digital technologies and robotics is transforming timber prefabrication from traditional subtractive CNC machining into a highly precise, additive, and collaborative process. The purpose of this project is to conduct a systematic literature review of the state of-the-art and near-future developments of automation and robotics in timber …

The Electric Crackdown: Exploring The Human Factors Impacts Of Controls & Displays In Evs Across The Market, Rae Okada, Robin Hanen, Liam Brennan

Discovery Day - Daytona Beach

Title: The Electric Crackdown: Exploring the Human Factors Impacts of Controls & Displays in Electric Vehicles Across the Market   Despite a global adoption of electric vehicles (EVs) with partial driving automation (i.e., advanced driver assistance systems; ADAS), differences exist at societal (i.e., legislation, regulation), individual (i.e., use of), and system (i.e., vehicle-to-vehicle) levels surrounding these vehicles. While these former societal divergences can be considered based on the: (1) mechanisms promoting or limiting EV adoption, (2) number of EVs on the road, and (3) respective incident reports; system differences require investigation for each vehicle based on its make and model. In …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Enhancing Virtual Reality Cockpit Procedure Training With Haptic Feedback, Christian K. Jaedicke

Doctoral Dissertations and Master's Theses

Pilot training is time-consuming and costly, and not all phases require full-flight simulators or actual aircraft. Virtual reality (VR) offers a potential means to reduce cost and duration while supporting practical cockpit procedure training. While prior research in the VR domain suggests that providing haptic feedback can support training of muscular control and increase perceived immersion, it remains unclear whether haptic feedback improves spatial cognition in an unfamiliar VR environment. This study examined whether haptic feedback and cockpit complexity affected response time and position error under limited-visibility, time-constrained conditions in a VR cockpit environment (i.e., a quasi-blindfold cockpit check).

Grounded …

Noise-Optimized Routes For Air Taxi, Waleed Raza

Doctoral Dissertations and Master's Theses

Community noise is a primary barrier to the public acceptance and deployment of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) air taxi operations. This dissertation develops a coupled siting, routing, and noise optimization framework that links vertiport placement to its downstream acoustic consequences, demonstrated through a Daytona Beach case study. Candidate vertiports are screened and selected using accessibility, safety, demand, and feasibility criteria, and the selected sites form a directed network of 20 routes. Each trajectory is evaluated with a physics-based acoustic pipeline reporting Lmax, SEL, and EPNL at school, hospital, and residential receptors, showing that received exposure …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Robust Real-Time Uav Target Tracking With Onboard Vision-Based Yaw Control, Rylan Malarchick, Jose Castelblanco, Enrique Amaya, Carmen Dimario, Graysen Brinkman, Chirag Kumar, Kiwon Yoon, Sajid Berhane

Beyond: Undergraduate Research Journal

Autonomous tracking of agile unmanned aerial vehicles (UAVs) presents significant challenges for real-time perception and control systems. This work presents AIRHOUND (Autonomous Intelligent Rotorcraft for Hostile Object Unified Navigation and Detection), a UAV platform implementing vision-based yaw tracking through a modular ROS2 software architecture. The system employs YOLOv8 object detection optimized with NVIDIA TensorRT for embedded deployment on an NVIDIA Jetson Orin companion computer. Detected targets are processed through a geometric tracking module that converts pixel coordinates to angular yaw errors using pinhole camera intrinsics, with a proportional controller generating rate-limited yaw commands. These commands are streamed to a PX4 …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla

Doctoral Dissertations and Master's Theses

While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and doubt induction, affects linguistic tone, objective accuracy, and internal calibration. A 1,080-trial experimental matrix evaluated six diverse models across factual, logical, coding, and cyber security domains. Analysis using the Kruskal-Wallis H-test revealed highly significant behavioral shifts across all measured dimensions, providing conclusive evidence that the applied frames exert a substantial influence on model performance.

The findings identify a distinct cognitive …

Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting, Madison Gleydura

Doctoral Dissertations and Master's Theses

Flash flood nowcasting in Central and Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at long range and signal blockage by mountains. GNSS-meteorology offers an established alternative for measuring precipitable water vapor and is currently integrated into several numerical weather models. Recent research demonstrates that commercial-grade GNSS receivers can produce tropospheric products comparable to those from geodetic-grade equipment. The gaps in mountain coverage can be addressed by developing a low-cost, self-contained embedded system that …

A Data-Driven Framework For Modeling Car-Following Behavior Using Conditional Transfer Entropy And Dynamic Mode Decomposition, Poorendra Ramlall

Student Research Symposium (SRS)

Accurate modeling of car-following behavior is essential for understanding traffic dynamics and enabling predictive control in intelligent transportation systems. This study presents a novel data-driven framework that combines information-theoretic input selection via conditional transfer entropy (CTE) with dynamic mode decomposition with control (DMDc) for identifying and forecasting car-following dynamics. In the first step, CTE is employed to identify the specific vehicles that exert directional influence on a given subject vehicle, thereby systematically determining the relevant control inputs for modeling its behavior. In the second step, DMDc is applied to estimate and predict the dynamics by reconstructing the closed-form expression of …

A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane

Doctoral Dissertations and Master's Theses

This research presents a quantitative performance comparison between light detection and ranging (LiDAR) and vision-based sensing for real-time maritime object detection on autonomous surface vessels. Using Embry-Riddle Aeronautical University’s (ERAU) Minion platform and 2024 Maritime RobotX Challenge data, this study evaluates the detection of six maritime object categories using two representative models. YOLOv8 provides a neural network vision-based method, and GB-CACHE provides a deterministic LiDAR-based method. Both models have been previously demonstrated to run in real time on uncrewed surface vessels (USVs). The evaluation methodology encompasses multi-sensor calibration, real-time performance analysis, and the introduction of a late-fusion strategy in the …

Exploration Of Physics-Informed Grid Generation Technique For Wall-Modeled Les Using Eagle3d, Dominic Schneider

Doctoral Dissertations and Master's Theses

Wall-Modeled Large Eddy Simulation (WMLES) is an area of interest due to its ability to lower computational costs of LES. Even with the application of wall models, LES still proves to have practicality issues when it comes to use in industry, due to the expertise, time, and computational resources required. A novel technique for generating a lean, physics based WMLES grid is described.

The technique utilizes a RANS solution to extract turbulence information, user-specified values related to resolution of turbulent energy levels, acoustics waves, and shock waves, to generate a point cloud for producing a lean WMLES grid with in-house …

Orbital Maneuvers And Interplanetary Trajectory Design Via Reinforcement Learning, Roberto Cuéllar Rangel

Doctoral Dissertations and Master's Theses

This dissertation investigates the application of reinforcement learning (RL) to the design and optimization of low-thrust spacecraft trajectories, with an emphasis on autonomy, adaptability, and robustness in the presence of system uncertainties and unmodeled perturbations. Classical approaches to low-thrust trajectory design are predominantly grounded in optimal control theory, which relies on the availability of precise dynamical models and often requires problem-specific reformulation and solver tuning. While optimal control methods offer high accuracy under deterministic conditions, their sensitivity to stochastic disturbances and computational limitations in highly nonlinear or uncertain environments pose significant challenges for future autonomous space missions.

To address these …