Show simple item record

dc.contributor.advisorJohansen, Tor Arnenb_NO
dc.contributor.authorStokkeland, Martinnb_NO
dc.date.accessioned2014-12-19T14:10:45Z
dc.date.available2014-12-19T14:10:45Z
dc.date.created2014-09-06nb_NO
dc.date.issued2014nb_NO
dc.identifier744160nb_NO
dc.identifierntnudaim:10734nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/261394
dc.description.abstractThis thesis studies the mission of autonomous inspection of a wind turbine using a multicopter. Emphasis was placed on recognition and tracking using image processing methods. The Hough line transform was used to extract features of the wind turbine. Hub position was estimated by an algorithm tailored to identify the three-point star resemblance and was tracked by utilizing the Kalman filter. Distance and yaw orientation of the wind turbine were estimated using the pinhole camera model and coordinate transformations. Restricting computational demand was a goal in the program design. Experiments showed accurate position tracking at long range, but with deteriorating performance as range was decreased. Lack of distinctive measurable lengths in the image caused inaccuracy in estimation of distance and yaw orientation. Execution frequency of below 7 Hz was achieved on a single-board computer which was found to be sufficient for reliable control in flight.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for teknisk kybernetikknb_NO
dc.titleA Computer Vision Approach for Autonomous Wind Turbine Inspection using a Multicopternb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber124nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikknb_NO


Files in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record