Graduation Semester and Year

2019

Language

English

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Yan Wan

Second Advisor

Yan Wan

Third Advisor

Atilla Dogan

Abstract

This work focuses on the roles of on-board sensing and off-board sensing through wireless communication for UAV missions. Employing UAV path planning under spatiotemporal wind effect as a case study, this work implements a modeling framework composed by the vehicle dynamics, environmental effect and communication model that transmits wind field data. Based on the analysis of the minimum-time optimal UAV path planning solution under communication constraints and spatiotemporal wind impact, this work obtains quantitative insights into the effect of communication quality and information update configuration on the performance of path planning. This study finds that on-board sensing and off-board sensing can both enhance the planning performance, however the performance of off-board sensing deteriorates as the communication conditions progressively get worse. Moreover, the path planning performance can be optimized if the information update parameters are correctly chosen subject to the channel capacity constraints. Ultimately, this work designs and validates an UAV navigation system which is an initial and essential step for a practical implementation of the path planning developed in this documents.

Keywords

UAV communication, UAV path planning

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

Download

Share

COinS