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Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline Aug 2026

Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline

Discovery Day - Daytona Beach

The increasing complexity of public safety operations in urban and high-density environments necessitates intelligent, mobile surveillance systems capable of real-time threat identification and situational awareness. Traditional monitoring approaches, such as fixed CCTV systems and manual observation, are often limited by coverage, scalability, and response latency in complex environments or large-scale events. This project addresses these challenges through the development of a computer vision-enabled Uncrewed Aerial System (UAS) designed for crowd monitoring and firearm detection. The primary objective is to design and validate a modular, Artificial Intelligence (AI)-Machine Learning (ML)-driven model capable of identifying firearms within dynamic environments while supporting real-time …

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Characterizing Air Traffic Density Using Nationwide Ads-B Data, Taeyun Yoo, Arjun Nambiar, Sang-A Lee Aug 2026

Characterizing Air Traffic Density Using Nationwide Ads-B Data, Taeyun Yoo, Arjun Nambiar, Sang-A Lee

Discovery Day - Daytona Beach

This study addresses the increasing need to understand aircraft activity in low-altitude airspace, where emerging operations such as Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) are expected to heighten traffic complexity and safety risks. This research develops a scalable framework for constructing a nationwide, high-resolution, altitude-stratified airspace density atlas using Automatic Dependent Surveillance–Broadcast (ADS-B) data. The methodology incorporates large-scale data acquisition, terrain-referenced altitude normalization, and spatial aggregation using a hexagonal grid system, followed by statistical modeling to estimate traffic density across spatial and temporal dimensions. Preliminary results indicate the capability to generate detailed geospatial representations of aircraft activity, …

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Investigation Of Bio-Inspired Design Tools In Satellites, Spoorti Nanjamma Aug 2026

Investigation Of Bio-Inspired Design Tools In Satellites, Spoorti Nanjamma

Discovery Day - Daytona Beach

This study investigates the application of Biologically Inspired Design (BID) tools within student-led satellite design teams, with the goal of enhancing early-stage systems engineering practices. As CubeSat missions become increasingly complex and resource-constrained, there is a need for approaches that support innovative yet structured problem-solving. While BID has shown promise in other engineering domains, its practical integration into satellite design, remains limited. To address this gap, three interactive workshops were developed and implemented with a Embry-Riddle Aeronautical university CubeSat team – Project COMET. The first workshop focused on functional decomposition, guiding students to express subsystem behavior in verb–noun form and …

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Model-Based Systems Engineering Test Case Development And Traceability For Cubesats, Spoorti Nanjamma, Abigail Butcher Aug 2026

Model-Based Systems Engineering Test Case Development And Traceability For Cubesats, Spoorti Nanjamma, Abigail Butcher

Discovery Day - Daytona Beach

Model-Based Systems Engineering (MBSE) using CATIA Magic Systems of Systems Architect (formerly known as CAMEO) is applied to develop a structured and traceable approach to test case modeling for CubeSat missions. The effort focuses on supporting unit-, subsystem-, and system-level testing by explicitly linking system requirements to corresponding test cases within the model, ensuring clear traceability across all verification levels. Each test case is organized within a dedicated package that includes a Block Definition Diagram (BDD) and Internal Block Diagram (IBD) to represent the complete test configuration, capturing all relevant components, subsystem boundaries, and interface connections involved in the test …

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Human-Centered Modeling Of Traffic As A Complex System, Poorendra P. Ramlall Aug 2026

Human-Centered Modeling Of Traffic As A Complex System, Poorendra P. Ramlall

Discovery Day - Daytona Beach

Traffic systems are driven not only by motion, but by interaction: vehicles influence one another, drivers continuously adapt to surrounding behaviour, and cognitive processes shape decisions that can propagate through the flow of traffic. Understanding these layered interactions is essential for improving traffic safety and for designing the next generation of intelligent, connected, and automated transportation systems. This PhD research develops a multiscale, data-driven framework for identifying, modelling, and ultimately interpreting interaction structure in traffic systems. The work first established an information-theoretic basis for this problem, demonstrating how information flow can uncover directional relationships in traffic dynamics and help infer …

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Selfish Herd: Emergence Of Distributed Sensing, Timothy Mascal Aug 2026

Selfish Herd: Emergence Of Distributed Sensing, Timothy Mascal

Discovery Day - Daytona Beach

The problem of multi-agent swarm formation control seeks decision frameworks that exhibit desirable emergent behavior, including distributed sensing and communication, while remaining resilient to environmental noise. Previous work has demonstrated that the Selfish Herd Model is not only resilient to simulated sensor noise but performs better in its presence. This work further investigates the emergent behaviors of the Selfish Herd Model, particularly distributed sensing, by investigating whether the swarm achieves global stability equivalent to that observed in previous work utilizing global knowledge. A parameter variation study was performed across varying agent visual range and maximum neighbor count inputs to simulate …

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Designing And Evolving The Life Support System For Spacex Starship: Toward Closed-Loop Sustainability For Mars Missions, Frányerson R. López Ochoa Aug 2026

Designing And Evolving The Life Support System For Spacex Starship: Toward Closed-Loop Sustainability For Mars Missions, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

The development of a robust Life Support System (LSS) is essential for enabling long-duration human spaceflight beyond Low Earth Orbit (LEO), particularly for missions to Mars. SpaceX Starship represents a next-generation spacecraft designed to support such missions; however, its Environmental Control and Life Support System (ECLSS) remains under active development. This work evaluates the current status of Starship’s LSS by analyzing publicly available data, NASA Human Landing System requirements, and heritage systems such as the International Space Station (ISS) ECLSS and Crew Dragon.

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Commercial Space Mining: From Competitive Secrecy To Transparency, Sustainability, And Governance Challenges In The New Race For Extraterrestrial Resources, Frányerson R. López Ochoa Aug 2026

Commercial Space Mining: From Competitive Secrecy To Transparency, Sustainability, And Governance Challenges In The New Race For Extraterrestrial Resources, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

Commercial space mining is becoming integral to the space economy, driven by the need for resources such as water, metals, and platinum-group metals (PGMs) from asteroids and the Moon. It should be noted that these resources have the potential to support long-duration space missions through in-situ resource utilization (ISRU) and Earth-based economic activities. Companies such as AstroForge and TransAstra are leading this transition, from government-led exploration to commercial activity. The paper examines the environmental, technological, and legal implications of asteroid mining, using these companies as case studies. While AstroForge has progressed to in-space demonstrations with its Odin spacecraft in 2025 …

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Atmospheric Gas Dynamics Of Mars: A Multi-Sensor Remote Sensing Approach For Fine Vertical, Global, And Event-Driven Analysis, Frányerson R. López Ochoa Aug 2026

Atmospheric Gas Dynamics Of Mars: A Multi-Sensor Remote Sensing Approach For Fine Vertical, Global, And Event-Driven Analysis, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

To provide precise vertical resolution and worldwide coverage across all seasons and altitudes, this study integrated nadir, limb, occultation, and general circulation model (GCM) measurements in a thorough remote sensing examination of the Martian atmosphere. The study examined the density and temperature structures of major atmospheric gases, mainly carbon dioxide (CO₂), molecular nitrogen (N₂), and argon (Ar), using mission datasets from the Mars Reconnaissance Orbiter (MRO), Mars Express (MEX), and the ExoMars Trace Gas Orbiter (TGO). It also assessed retrieval uncertainties resulting from dust, ice clouds, and sensor limitations. The study concluded that, though valuable, single-geometry observation techniques are unable …

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Optimization Of Co₂ Removal In Carbon Dioxide Removal Assembly (Cdra) Using Nonlinear Equilibrium Modeling And Zeolite-Based Adsorption Simulation, Frányerson R. López Ochoa Aug 2026

Optimization Of Co₂ Removal In Carbon Dioxide Removal Assembly (Cdra) Using Nonlinear Equilibrium Modeling And Zeolite-Based Adsorption Simulation, Frányerson R. López Ochoa

Discovery Day - Daytona Beach

This study follows a quantitative, non-experimental, existing-data design to examine the optimization of carbon dioxide removal in spacecraft’s Carbon Dioxide Removal Assembly (CDRA) through the integration of nonlinear isotherm modeling and process-level cycle simulation. Existing carbon dioxide adsorption equilibrium data from multiple zeolite sorbents, including Grace Davison Grade (544 13X, 522 5A, and 514 4A), Honeywell UOP (APG-III, LiLSX VSA-10), and BASF 13X, is analyzed to determine which adsorption models best represent carbon dioxide loading behavior and how these models can be used to reduce energy consumption in spacecraft regeneration processes. The study fitted eight nonlinear isotherm models – Langmuir, …

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Enhancing Fibre–Matrix Interface Properties In Cfrps Using Cohesive Zone Modelling, Arjun Myadam, Alexander Skoppe Aug 2026

Enhancing Fibre–Matrix Interface Properties In Cfrps Using Cohesive Zone Modelling, Arjun Myadam, Alexander Skoppe

Discovery Day - Daytona Beach

Carbon fibre reinforced polymers (CFRPs) are extensively used in aerospace, automotive, and structural applications owing to their high specific strength, stiffness, and design flexibility. The mechanical performance of these composites is critically governed by the fibre–matrix interface, which controls stress transfer and directly influences damage initiation, crack propagation, and fracture behaviour. The interface strength is quantified through the interfacial shear strength (IFSS) and fracture energy, both serving as key indicators of composite integrity. Nanoscale fibre surface modifications are widely employed to enhance interfacial bonding and can also impart multifunctionality, such as capacitive properties, magnetic behaviour, and piezoelectricity. For instance, nanoscale …

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N31 Multi-Sensor Data Fusion For Enhanced Cislunar Space Domain Awareness Using Radar And Optical Observations, Lucas Bottero Aug 2026

N31 Multi-Sensor Data Fusion For Enhanced Cislunar Space Domain Awareness Using Radar And Optical Observations, Lucas Bottero

Discovery Day - Daytona Beach

MULTI-SENSOR DATA FUSION FOR ENHANCED CISLUNAR SPACE DOMAIN AWARENESS USING RADAR AND OPTICAL OBSERVATIONS   As operations extend into cislunar space, maintaining Space Domain Awareness (SDA) becomes increasingly challenging due to the vast distances, sparse infrastructure, and complex gravitational dynamics between Earth and the Moon. Radar and optical sensors are the primary modalities used for space surveillance, each with its strengths and limitations. Radar offers continuous observation capabilities regardless of lighting conditions but is limited by power and range at cislunar distances. Optical sensors provide high angular precision but depend on favorable illumination and line-of-sight geometry. However, there has been limited …

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Modeling A Spaceborne Passive Radar Architecture For Tracking Resident Space Objects Using Ground-Based Signals Of Opportunity, Chinmay Gaikwad Aug 2026

Modeling A Spaceborne Passive Radar Architecture For Tracking Resident Space Objects Using Ground-Based Signals Of Opportunity, Chinmay Gaikwad

Discovery Day - Daytona Beach

Modeling a Spaceborne Passive Radar Architecture for Tracking Resident Space Objects Using Ground-Based Signals of Opportunity Due to an increase in manned and unmanned space activities, there is an increase in demand for resilient space operations. This project investigates passive-radar architecture for space domain awareness in which satellites in a low-Earth-orbit mega-constellation are adapted as distributed sensing platforms for tracking debris and other non-cooperative resident space objects. The motivation is to overcome the coverage, cost, and scalability limits of conventional active or ground-based systems by using lightweight passive receivers that exploit ground-based illuminators of opportunity. In this concept, the receivers …

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Using Sysml Models To Verify System Design And Identify Discrepancies In A Satellite System, Noah Fulton Aug 2026

Using Sysml Models To Verify System Design And Identify Discrepancies In A Satellite System, Noah Fulton

Discovery Day - Daytona Beach

This study investigates the use of Systems Modeling Language (SysML) to verify subsystem design consistency and identify integration discrepancies in a multidisciplinary satellite program. Project COMET, an Embry-Riddle effort under the University Nanosatellite Program (UNP), consists of six subsystems but lacks a centralized system model. This leads to inconsistencies between subsystem inputs, outputs, and interface definitions. Typically, SysML models are created early in the system design cycle; However, this study will evaluate how creating system models post preliminary design review (PDR) can assist a project by verifying subsystem integration or by identifying discrepancies between independently developed subsystems. This study will …

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Environmental Ethics Of Plastics And Microplastics Manufacturing: Balancing Industrial Production And Ecological Responsibility, Arindam Gupta Aug 2026

Environmental Ethics Of Plastics And Microplastics Manufacturing: Balancing Industrial Production And Ecological Responsibility, Arindam Gupta

Discovery Day - Daytona Beach

The global production of plastics has increased dramatically over the past several decades, providing substantial economic and societal benefits while simultaneously generating complex environmental and ethical challenges. A growing body of research has identified microplastics—plastic particles smaller than 5 millimeters—as persistent pollutants that accumulate in aquatic ecosystems, soil systems, and the atmosphere. These particles originate both from the degradation of larger plastic products and from direct industrial production processes used in plastics manufacturing. The ethical implications of plastics and microplastics production raise important questions about environmental responsibility, regulatory oversight, and the balance between economic development and ecological sustainability. This project …

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Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers, Santiago Acuna Gonzalez Aug 2026

Spatial Dynamics Of Lead Waste: An Esda Approach To U.S. Interstate Transfers, Santiago Acuna Gonzalez

Discovery Day - Daytona Beach

Spatial Dynamics of Lead Waste: An ESDA Approach to U.S. Interstate Transfers   This research applied a novel Exploratory Spatial Data Analysis (ESDA) methodology to analyze interstate movements (n= 446) of lead (Pb; CAS 7339-92-1) among facilities that transported more than 1,000 lbs offsite across the United States, using the Environmental Protection Agency’s (EPA) 2024 Toxic Release Inventory (TRI). Using QGIS, the analysis produced three geospatial products by integrating TRI Form R Schedule 3A with coordinates from the EPA Facility Registry Service (FRS) to populate offsite locations. First, a state-level net-flow choropleth distinguished exporting from importing states. Second, an export-focused map …

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Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang Aug 2026

Environmental Ethics And Impact Of Artificial Intelligence Data Centers, Jacky Yang

Discovery Day - Daytona Beach

Data centers, including artificial intelligence (AI) facilities, serve as the backbone for many modern digital services and products. With the rapid digitization of society, the expansion of these centers in the United States has accelerated significantly. From an anthropocentric and utilitarian perspective, they provide economic benefits, supporting employment and generating public revenue. However, they can also create a significant amount of environmental and societal challenges. From an ecocentric and environmental justice perspective, AI data centers has contributed to increased competition for the limited resources, such as water, electricity, and land and has been linked to rising utility costs, noise pollution, …

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Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder Aug 2026

Quantitative Analysis Of A Single Operator’S Flight Behavior In Simulation, Zackrey Schraeder

Discovery Day - Daytona Beach

Uncrewed Aircraft Systems (UAS), or more commonly known as drones, have become increasingly used for a variety of applications, and more research has emerged studying the human-machine interaction and pilot performance metrics. Current research focuses on desired behaviors or aggregated pilot data which does not provide a holistic picture of an individual pilot’s flight behaviors, which are shaped by their own experience, preferences, and risk tolerance. The study investigates whether an individual pilot’s flight behaviors can be considered a pattern or if there is enough flight-to-flight variability to consider the behaviors inconsistent. A series of 20 flights were conducted in …

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Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder Aug 2026

Modernization Of Deicing Operations Utilizing Uncrewed Aircraft Systems, Christopher Sidor, Hunter Lisle, Zackrey Schraeder

Discovery Day - Daytona Beach

Modernization of Deicing Operations Utilizing Uncrewed Aircraft Systems   The use of Uncrewed Aircraft Systems (UAS), commonly known as drones, has become more apparent in everyday life within the United States (US). The Airport Cooperative Research Program (ACRP) has provided an opportunity to utilize drones to improve quality of life and operational efficiency at airports across the US. Students from Embry-Riddle Aeronautical University under the callsign Team Frostbite, consists of Hunter Lisle, Zakrey Schraeder, and Christopher Sidor. The team provides a potential solution utilizing UAS to measure the efficiency of deicing applications at Patrick Leahy Burlington International Airport (BTV) in Burlington, …

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Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz Aug 2026

Quantifying Grain Size In Scanning Electron Microscopy Images, Katherine Hoffsetz

Discovery Day - Daytona Beach

This project explores advanced image analysis techniques to assess the microstructure of highly strained austenitic stainless steel. Utilizing Python imaging libraries such as scikit-image and OpenCV, we aim to extract precise measurements for grain size from scanning electron microscopy (SEM) images. These metrics will be examined against the computed grain sizes of the sample from electron backscatter diffraction measurements. By automating the extraction of grain size measurements from SEM images, this study contributes to steamlining the quality assurance/ quality control of industrially processed materials.

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Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth Aug 2026

Learning Casual Structures From Aviation Accident Narratives Using Natural Language Processing And Graph-Based Knowledge Representation, Stephanie Ramsey, Katherine Hoffsetz, Madeline Gorman, Logan Lambeth

Discovery Day - Daytona Beach

Understanding the complex causal relationships underlying aviation accidents is critical for improving safety and preventing future incidents. However, much of this information exists in unstructured narrative reports, making large-scale analysis difficult. This project aims to automatically extract and model causal chains from National Transportation Safety Board (NTSB) accident narratives using a combination of traditional natural language processing (NLP) techniques, transformer-based architectures, and graph-based knowledge representation. Traditional NLP methods, including named entity recognition, dependency parsing, and rule-based pattern matching, will be used to identify structured cause–effect relationships. These approaches will be compared with transformer-based models, including a lightweight encoder for classification …

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Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender Aug 2026

Exploring Generation Z Pilots' Approach To Training Automation: An Interview Study, Mary Bender

Discovery Day - Daytona Beach

Introduction. Today's pilots learn to fly on aircraft with sophisticated automated systems, such as the G1000. Although automation can reduce workload, over-relying on this technology can lead to decreased situational awareness, complacency, and a loss in manual flying skills (Parasuraman, 2000; Parasuraman et al., 2000; Parasuraman & Wickens, 2017; Taylor et al., 2020). Instructor pilots, in turn, are faced with the challenge of teaching students how to leverage a system that can affect their performance, both positively and negatively. The purpose of this study was to explore the strategies and challenges that instructor pilots face when training students on automation. …

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High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin Aug 2026

High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin

Discovery Day - Daytona Beach

Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …

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Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon Aug 2026

Quantitative Assessment Of Cybersecurity Risk Variability Across Transportation Modes, Paulo Carreon

Discovery Day - Daytona Beach

Quantitative Assessment of Cybersecurity Risk Variability Across Transportation Modes examines how cybersecurity risks differ across major transportation sectors and addresses the lack of a structured, cross modal analysis in existing transportation cybersecurity research. As transportation systems increasingly rely on digital infrastructure, communication networks, operational technologies, and interconnected platforms, they become more exposed to cyber threats that can affect safety, mobility, operations, and public trust. Despite the growing importance of this issue, there is still limited research that quantitatively compares how cyber risks vary across transportation modes such as road and intelligent transportation systems, aviation, rail and transit, and maritime systems. …

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Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala Aug 2026

Small Unmanned Aerial Systems-Assisted Airport Obstruction And Perimeter Inspections, Christopher Candler, Christopher M. Saylor, Marcus Thompson, Tejash Zala

Discovery Day - Daytona Beach

Airports are required to maintain obstruction-free airspace surfaces under 14 CFR Part 77; however, vegetation and perimeter obstruction management is often conducted through periodic ground inspections and contractor-led surveys that provide only snapshot conditions. These approaches may delay detection of encroachments into approach, transitional, horizontal, or primary surfaces, increasing the risk of operational impacts and reactive mitigation. This study proposes an FAA-aligned framework integrating small unmanned aircraft systems (sUAS) into obstruction monitoring workflows through recurring, repeatable perimeter inspections. High-resolution optical and LiDAR sensors, combined with RTK/PPK-enabled GNSS correction, generate centimeter-level geospatial datasets that are processed into canopy height models. These …

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Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang Aug 2026

Advancing Runway Incursion Severity Prediction Through Tabular-To-Image Deep Learning, Bill Deng Pan, Yupeng Yang

Discovery Day - Daytona Beach

Runway incursions remain one of the most persistent safety challenges in modern aviation operations, often resulting from complex interactions among human, environmental, and operational factors. While existing Safety Management System (SMS) frameworks emphasize monitoring the frequency of incursions, they provide limited predictive capability regarding event severity. This ongoing study seeks to address that gap by applying a novel tabular-to-image deep-learning approach to improve the accuracy and interpretability of runway-incursion severity prediction models. Data for this study will be drawn from the Federal Aviation Administration (FAA) Runway Safety Statistics and National Transportation Safety Board (NTSB) accident databases. The methodology will involve …

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Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan Aug 2026

Assessing Safety Culture Among Airport Operators Through Stakeholder Perceptions, Bill Deng Pan

Discovery Day - Daytona Beach

The effective implementation of Safety Management Systems (SMS) at airports depends not only on compliance with regulatory requirements but also on the presence of a strong and measurable safety culture. While the Federal Aviation Administration (FAA)’s increasing emphasis on SMS has accelerated adoption across certificated airports, many airport operators, often coming from operational, engineering, or business backgrounds, lack practical methods to assess safety culture in a structured and actionable manner. Existing guidance highlights the importance of safety culture and safety climate. However, limited research exists on how airport stakeholders perceive and experience safety culture within the airport operating environment. This …

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Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison Aug 2026

Sequential Causal Architecture For Multimodal Aviation Accident Prediction, Kaitlyn Cavanaugh, Isaac Morrison

Discovery Day - Daytona Beach

Aviation accidents are rarely the result of a single failure but rather from a complex causal chain of latent failures. While traditional data mining models often predict incident occurrence, they frequently overlook the sequential mechanics defined by known accident causation theoretical frameworks like the Swiss Cheese Model and the FAA's HFACS. This project addresses the need for interpretable, reliable, multi-stage forecasting by proposing a Sequential Causal Architecture that transforms theoretical causation models into a structured Directed Acyclic Graph (DAG) for multimodal accident causation chain prediction. Data from the NTSB and DOT is used and connected together in a meaningful way …

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Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin Aug 2026

Energy-Aware Bimodal Contact Detection For Leg Odometry, Emre Girgin

Discovery Day - Daytona Beach

Autonomous exploration of extraterrestrial environments using legged robots requires robust GNSS-free 3D state estimation. Standard leg odometry relies on Zero-Velocity Updates (ZUPT), which assume a grounded foot remains completely stationary. This assumption consistently fails on deformable granular terrain due to unobservable slippage, rapidly degrading state estimation. To mitigate this critical failure mode, we propose a dual contact-detection framework designed to robustly gate an Error-State Extended Kalman Filter (ESEKF) tracking pose, velocity, and IMU biases.   The architecture isolates physical load and kinematics by modeling contact detection as two independent parallel Hidden Markov Models (HMMs). The Load HMM processes Ground Reaction Forces, …

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Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak Aug 2026

Heuristic Trafficability Assessment For Autonomous Lunar Surface Operations Using Orbital Data Products, Leia Spaniak

Discovery Day - Daytona Beach

This study seeks to map the surface of the Moon by developing a new orbital dataset composed of layers that inform trafficability. The project supports the objectives of the Artemis Program by focusing operations on the Lunar South Pole, where terrain conditions remain difficult to assess over broad areas. With future validation anticipated through cone penetrometer testing, the study examines what orbital data layers can reveal about bearing capacity through estimated internal friction angle, density, and cohesion. The research evaluates the feasibility of this methodology by comparing the mapping strategy to data obtained during the Apollo 15, 16, and 17 …

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