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dc.contributor.authorFrauenthal, Jay Matthewen_US
dc.date.accessioned2015-09-18T19:58:48Z
dc.date.available2015-09-18T19:58:48Z
dc.date.issued2015-09-13en_US
dc.identifier.othervt_gsexam:6096en_US
dc.identifier.urihttp://hdl.handle.net/10919/56559
dc.description.abstractRailroad tracks require consistent and periodic monitoring to ensure safety and reliability. Unmanned Aerial Vehicles (UAVs) have great potential because they are not constrained to the track, allowing trains to continue running while the UAV is inspecting. Also, they can be quickly deployed without human intervention. For these reasons, the first steps towards creating a track-monitoring UAV system have been completed. This thesis focuses on the design of algorithms to be deployed on a UAV for the purpose of monitoring the health of railroad tracks. Before designing the algorithms, the first steps were to design a rough physical structure of the final product. A small multirotor or fixed-wing UAV will be used with a gimbaled camera mounted on the belly. The camera will take images of the tracks while the onboard computer processes the images. The computer will locate the tracks in the image as well as perform defect detection on those tracks. Algorithms were implemented once a rough physical structure of the product was completed. These algorithms detect and follow rails through a video feed and detect defects in the rails. The rail following algorithm is based on a custom-designed masking technique that locates rails in images. A defect detection algorithm was also created. This algorithm detect defects by analyzing gradient data on the rail surface.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectUASen_US
dc.subjectComputer Visionen_US
dc.subjectRailroad Health Monitoringen_US
dc.subjectImage Transformationen_US
dc.subjectDefect Detectionen_US
dc.titleDesign and Exploration of a Computer Vision Based Unmanned Aerial Vehicle for Railroad Health Applicationsen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreeMSen_US
thesis.degree.nameMSen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairKochersberger, Kevin Bruceen_US
dc.contributor.committeememberSouthward, Steve Cen_US
dc.contributor.committeememberParikh, Devien_US


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