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Articles 1 - 10 of 10
Full-Text Articles in Multi-Vehicle Systems and Air Traffic Control
Multimodal Interpretation Of Pilot–Controller Communications For Runway Safety Assurance And Enhanced Atc Situational Awareness., Chaebin Song, Juin Park
Multimodal Interpretation Of Pilot–Controller Communications For Runway Safety Assurance And Enhanced Atc Situational Awareness., Chaebin Song, Juin Park
Discovery Day - Daytona Beach
Recent runway safety events have highlighted the importance of accurate and timely interpretation of pilot–controller communications, especially in complex airport environments where aircraft and ground vehicles interact on or near active movement areas. In light of the recent LaGuardia Airport collision, which has drawn attention to communication, coordination, and surface safety challenges, this project investigates how multimodal data can support air traffic controllers’ situational awareness and safety assurance. This study develops an in-progress framework that combines Automatic Speech Recognition (ASR) of pilot–controller radio communications with ADS-B trajectory data to improve interpretation of operational intent and cross-check communications against observed aircraft …
Improving Multi-Agent Swarm Collision Avoidance Using Reciprocal Velocity Obstacles, Nick Wilson
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
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 …
Applications Of A Swarm-Behavior Model On Existing Satellite Constellations, Naomi Lee
Applications Of A Swarm-Behavior Model On Existing Satellite Constellations, Naomi Lee
Discovery Day - Daytona Beach
The scope of this work explores biological swarm behavior and its application to low- and medium-sized Earth orbit satellite constellation systems. Existing constellation structures have predetermined orbits, meaning there is little adaptivity in the spacing and interactions between satellites. This allows for formation disruption by atmospheric perturbations in lower Earth orbit trajectories but can be countered with interactive controls that help with structure stability. This adaptive spacing and control can also be applied in MEO constellations in coverage and positioning optimization. In ‘mimicking’ this swarm behavior in starling murmurations, the separation, alignment, and cohesion flocking behavior of satellite groupings will …
Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk
Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk
Discovery Day - Daytona Beach
HELIO: Heliophysics Enhanced Learning for Intelligent Orbits Satellite constellations operating in near-Earth space are increasingly vulnerable to space weather disturbances, such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, which degrade communications, destabilize attitude control, and accelerate orbital decay. These disturbances directly threaten mission continuity, constellation availability, and space asset survivability. Current protective approaches rely primarily on ground-based alerts and lack integration with broader space domain awareness, which results in programmed reactive protocols that are often initiated too late to prevent performance degradation and asset loss. The HELIO project addresses this gap by turning space-weather forecasts …
Fault-Aware Flight Path Assessment For Evtols Using An Integrated Air Traffic Management Environment, John Clardy, Edison Alberto Martinez Samaniego
Fault-Aware Flight Path Assessment For Evtols Using An Integrated Air Traffic Management Environment, John Clardy, Edison Alberto Martinez Samaniego
Discovery Day - Daytona Beach
This study introduces a simulation framework to evaluate Fault-Aware Flight Paths for electric vertical takeoff and landing (eVTOL) aircraft within an integrated air traffic management environment. By combining an air traffic management system with intelligent trajectory generation frameworks, the approach assesses the development of safe, adaptive, and fault-aware flight paths that account for traffic interactions, airspace features, and specific operational constraints. Real-world historical airspace traffic data was used to accurately simulate complex and congested operational conditions. The main goal is to evaluate the operational impact of integrating eVTOL operations into the National Airspace System, with a focus on conflict detection, …
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Discovery Day - Daytona Beach
Title: Dual-Perspective Risk Analysis for Human-LLM Decision Comparison in UAV Swarm Navigation Unmanned aerial vehicle (UAV) swarms operating in low-altitude wireless network environments encounter localized disruptions that degrade positioning and navigation metrics. These disruptions are modeled as geographic failure zones with defined boundaries. A UAV discovers a zone by entering it and observing degraded performance on its onboard systems. This work assumes that affected UAVs can autonomously retreat to safety using onboard sensors and focuses on the subsequent rerouting decision. Once recovered, the system generates candidate repositioning points surrounding the vehicle, each scored using Conditional Value-at-Risk (CVaR). A human operator …
Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods
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 …
Accelerating Search And Rescue Response: A Simulation Study On The Dynamic Efficiency Of Flocking-Enabled Drone Swarms, Sophia Beckwith, Carys Del Prete
Accelerating Search And Rescue Response: A Simulation Study On The Dynamic Efficiency Of Flocking-Enabled Drone Swarms, Sophia Beckwith, Carys Del Prete
Discovery Day - Daytona Beach
This project explores how imitations observed in animal group behavior, specifically flocking in birds, can be applied to the functionality of autonomous drone systems to aid in search and rescue efforts. The goal is to demonstrate how incorporating code based on the Boids, Vicsck and predictive control linear algebraic mathematical models for drone flight controls and the collective behaviors of flocks will increase the efficiency of drone maneuvers, allowing them to reorganize and fill gaps when one is removed. A MATLAB-based simulation was developed to model the behaviors using research conducted on the symmetric and synchronized behaviors observed from flocks …
Interplay Between Physical Design Choices And Emergent Cyber System Consensus: A Case Study With An Underwater Swarm, Ava Neubert
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 …