Proof of Concept: Simulating Drone Tracking in a Border Security Context

Author

Jose Ruben Espinoza, The University of Texas Rio Grande Valley

Date of Award

12-1-2024

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Dong-Chul Kim

Second Advisor

Erik Enriquez

Third Advisor

Bin Fu

Abstract

Worldwide availability of drone technology has risen to unprecedented levels within the past century due to its commercial availability. While there has been various positive applications of such technology, it has additionally found usage within security critical contexts. Specifically, there have been reports of illegal drug smuggling along the Mexico-United States border in which quadrocopter based drones have been used. Within our research we aim to showcase, as a proof of concept, that autonomous drone technology can be leveraged within a defensive approach via the usage of reinforcement learning and object detection for security critical contexts. To promote the importance of the lens within our research, we provide a brief introduction within the realm of illegal drone usage. The following main experiments are explored: navigation of a drone to a particular target, following a target, utilizing an onboard camera depth based camera for target neutralization, and drone tracking via a custom object detection method. Simulations are developed through the usage of NVIDIA’s Isaac Gym technology while incorporating Aerial Isaac Gym. The object detection utilized within this research is derived from a small custom pre-trained YOLOv7 model.

Comments

Copyright 2024 Jose Ruben Espinoza. https://proquest.com/docview/3153400251

Recommended Citation

Espinoza, Jose Ruben, "Proof of Concept: Simulating Drone Tracking in a Border Security Context" (2024). Theses and Dissertations. 1638.
https://scholarworks.utrgv.edu/etd/1638