Abstract
In recent years, technological advances have shown a strive for more automated processes in agriculture, as seem with the use of unmanned aerial vehicles (UAVs) with onboard sensors in many applications, including disease detection and yield prediction. In this thesis, an octorotor UAV is presented that was designed, built, and flight tested, with features that are custom-designed for strawberry orchard disease detection. To further automate the disease scouting operation, geolocation, or the process of determining global position coordinates of identified diseased regions based on images taken, is investigated. A Kalman filter is designed, based on a linear measurement model derived from an orthographic projection method, to estimate the target position. Simulation, as well as an ad-hoc experiment using flight data, is performed to compare this filter to the extended Kalman filter (EKF), which is based on the commonly used perspective projection method. The filter is embedded onto a CPU board for real-time use aboard the octorotor UAV, and the algorithm structure for this process is presented. In the later part of the thesis, a probabilistic data association method is used, jointly with a proposed logic-based measurement-to-target correlation method, to analyze measurements of different target sources and is incorporated into the Kalman filter. A simulation and an ad-hoc experiment, using video and flight data acquired aboard the octorotor UAV with a gimballed camera in hover flight, are performed to demonstrate the effectiveness of the algorithm and UAV platform.
Notes
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Graduation Date
2016
Semester
Summer
Advisor
Xu, Yunjun
Degree
Master of Science in Aerospace Engineering (M.S.A.E.)
College
College of Engineering and Computer Science
Department
Mechanical and Aerospace Engineering
Degree Program
Aerospace Engineering; Space System Design and Engineering
Format
application/pdf
Identifier
CFE0006305
URL
http://purl.fcla.edu/fcla/etd/CFE0006305
Language
English
Release Date
August 2017
Length of Campus-only Access
1 year
Access Status
Masters Thesis (Open Access)
STARS Citation
Garcia, Christian, "Geolocation of Diseased Leaves in Strawberry Orchards for a Custom-Designed Octorotor" (2016). Electronic Theses and Dissertations. 5197.
https://stars.library.ucf.edu/etd/5197