Computer Science ETDs

John Ericksen

Publication Date

Spring 5-16-2025

Abstract

Volcanic systems are inherently complex, involving dynamic interactions among magma flow, gas emissions, and atmospheric dispersion. This dissertation focuses on developing and analyzing autonomous UAS algorithms for efficiently surveying volcanic CO2 plumes, introducing several novel methods: the LoCUS algorithm, a swarm coordination and self-healing algorithm that supports gradient-based plume tracking, a transect-based technique that employs a 2D Gaussian fit to calculate CO2 plume flux, and the Sketch algorithm for rapid plume boundary tracing. By treating multiple UAS as a single scientific instrument, these methods leverage swarm algorithms to use in-situ data in ways impossible with individual drones. Validated through simulations and field experiments at sites such as the Valles Caldera supervolcano in New Mexico and the Tajogaite eruption in La Palma, these techniques effectively find plume sources, calculate maximum CO2 plume flux, and map plume areas, all the while mitigating operational risks. Conducted under the VolCAN project, this research provides powerful tools for volcano monitoring and hazard prediction, with broader implications for studying environmental phenomena.

Language

English

Keywords

Swarm Robotics, Volcanic CO2, Drones, Plume Tracking, Flocking

Document Type

Dissertation

Degree Name

Computer Science

Level of Degree

Doctoral

Department Name

Department of Computer Science

First Committee Member (Chair)

Melanie E. Moses

Second Committee Member

Rafael Fierro

Third Committee Member

George Matthew Fricke

Fourth Committee Member

Kim Linder

Fifth Committee Member

Jared Saia

Download

Share

COinS