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dc.contributor.advisorYakimenko, Oleg A.
dc.contributor.authorTeo, Wei Shun
dc.date.accessioned2018-10-26T19:20:44Z
dc.date.available2018-10-26T19:20:44Z
dc.date.issued2018-09
dc.identifier.urihttp://hdl.handle.net/10945/60353
dc.descriptionApproved for public release. distribution is unlimiteden_US
dc.description.abstractUnmanned systems are gaining popularity in many modern-day applications, and their growth potential in unmanned technologies is infinite. These systems have created research and development opportunities for enabling autonomous behavior to reduce human workload and involvement in tedious operations. This thesis assesses autonomy-enabling technologies for conducting search-and-rescue (SA) operations and intelligence, surveillance, and reconnaissance (ISR) missions using a small unmanned system (sUAS). These technologies include an electro-optical sensor, onboard processor, and computer-vision (CV) algorithms. In a previous master’s thesis by Wee Kiong Ang, a commercial off-the-shelf (COTS) quadcopter sUAS was integrated with a suite of hardware and multiple-moving-target-detection software. Building upon that work, this thesis aims to advance the system’s capabilities by exploring the applicability of the aforementioned three technologies on an sUAS. Using the systems engineering approach, the baseline system deficiencies are identified first. Next, a technology enabler review is conducted to explore the relevant COTS products and paradigms. Then, through the implementation of a set of changes, the baseline system architecture is reassessed and consequently redesigned, followed by an assessment of state-of-the-art CV algorithms. After being tested in a field experiment based on SA/ISR-type mission scenarios, the developed prototype was found to be successful.en_US
dc.description.urihttp://archive.org/details/advancingcotsuav1094560353
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsCopyright is reserved by the copyright owner.en_US
dc.titleADVANCING COTS UAV CAPABILITY TO PROVIDE VISION-BASED SA/ISR DATAen_US
dc.typeThesisen_US
dc.contributor.secondreaderPapoulias, Fotis A.
dc.contributor.departmentSystems Engineering (SE)
dc.subject.authorunmanned aerial systemen_US
dc.subject.authorUAVen_US
dc.subject.authorcomputer visionen_US
dc.subject.authorobject detectionen_US
dc.subject.authoroptical-flowen_US
dc.subject.authorpayload sensoren_US
dc.subject.authormanifolden_US
dc.subject.authorGPUen_US
dc.description.recognitionOutstanding Thesisen_US
etd.thesisdegree.nameMaster of Science in Systems Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineSystems Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.identifier.thesisid29944


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