Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems
This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; there...
Main Author: | |
---|---|
Format: | Others |
Published: |
BYU ScholarsArchive
2021
|
Subjects: | |
Online Access: | https://scholarsarchive.byu.edu/etd/8998 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10007&context=etd |
id |
ndltd-BGMYU2-oai-scholarsarchive.byu.edu-etd-10007 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-BGMYU2-oai-scholarsarchive.byu.edu-etd-100072021-09-23T05:01:08Z Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems Morgan, Hayden Matthew This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; therefore, applications such as high-altitude visual searches for human motion often ignore target motion as noise. Furthermore, after a target is identified, arbitrary maneuvers for transitioning to overhead orbits for better observation may result in temporary or permanent loss of target visibility. We present guidelines for tuning parameters of the Visual Multiple Target Tracking (Visual MTT) algorithm to enhance its detection capabilities for very small, slow-moving targets in high-resolution images. We show that the tuning approach is able to detect walking motion of a human described by 10-15 pixels from high altitudes. An algorithm is then presented for defining rotational bounds on the controllable degrees of freedom of an aircraft and gimballed camera system for maintaining visibility of a known ground target. Critical rotations associated with the fastest loss or acquisition of target visibility are also defined. The accuracy of these bounds are demonstrated in simulation and simple applications of the algorithm are described for UAS. We also present a path planning and control framework for defining and following both dynamically and visually feasibly transition trajectories from an arbitrary point to an orbit over a known target for further observation. We demonstrate the effectiveness of this framework in maintaining constant target visibility while transitioning to the intended orbit as well as in transitioning to a lower altitude orbit for more detailed visual analysis of the intended target. 2021-05-27T07:00:00Z text application/pdf https://scholarsarchive.byu.edu/etd/8998 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10007&context=etd https://lib.byu.edu/about/copyright/ Theses and Dissertations BYU ScholarsArchive unmanned aircraft systems fixed-wing UAS vision-constrained control computer vision constrained path planning autonomous UAS flight visual target tracking small target tracking drones search and rescue Engineering |
collection |
NDLTD |
format |
Others
|
sources |
NDLTD |
topic |
unmanned aircraft systems fixed-wing UAS vision-constrained control computer vision constrained path planning autonomous UAS flight visual target tracking small target tracking drones search and rescue Engineering |
spellingShingle |
unmanned aircraft systems fixed-wing UAS vision-constrained control computer vision constrained path planning autonomous UAS flight visual target tracking small target tracking drones search and rescue Engineering Morgan, Hayden Matthew Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
description |
This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; therefore, applications such as high-altitude visual searches for human motion often ignore target motion as noise. Furthermore, after a target is identified, arbitrary maneuvers for transitioning to overhead orbits for better observation may result in temporary or permanent loss of target visibility. We present guidelines for tuning parameters of the Visual Multiple Target Tracking (Visual MTT) algorithm to enhance its detection capabilities for very small, slow-moving targets in high-resolution images. We show that the tuning approach is able to detect walking motion of a human described by 10-15 pixels from high altitudes. An algorithm is then presented for defining rotational bounds on the controllable degrees of freedom of an aircraft and gimballed camera system for maintaining visibility of a known ground target. Critical rotations associated with the fastest loss or acquisition of target visibility are also defined. The accuracy of these bounds are demonstrated in simulation and simple applications of the algorithm are described for UAS. We also present a path planning and control framework for defining and following both dynamically and visually feasibly transition trajectories from an arbitrary point to an orbit over a known target for further observation. We demonstrate the effectiveness of this framework in maintaining constant target visibility while transitioning to the intended orbit as well as in transitioning to a lower altitude orbit for more detailed visual analysis of the intended target. |
author |
Morgan, Hayden Matthew |
author_facet |
Morgan, Hayden Matthew |
author_sort |
Morgan, Hayden Matthew |
title |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
title_short |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
title_full |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
title_fullStr |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
title_full_unstemmed |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft Systems |
title_sort |
small-target detection and observation with vision-enabled fixed-wing unmanned aircraft systems |
publisher |
BYU ScholarsArchive |
publishDate |
2021 |
url |
https://scholarsarchive.byu.edu/etd/8998 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10007&context=etd |
work_keys_str_mv |
AT morganhaydenmatthew smalltargetdetectionandobservationwithvisionenabledfixedwingunmannedaircraftsystems |
_version_ |
1719482793502703616 |