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dc.contributor.supervisorCulverhouse, Phil
dc.contributor.authorTerzakis, George
dc.contributor.otherSchool of Engineering, Computing and Mathematicsen_US
dc.date.accessioned2016-11-08T10:04:15Z
dc.date.available2016-11-08T10:04:15Z
dc.date.issued2016
dc.identifier10224907en_US
dc.identifier.urihttp://hdl.handle.net/10026.1/6686
dc.description.abstract

This is a thesis on outdoor monocular visual SLAM in natural environments. The techniques proposed herein aim at estimating camera pose and 3D geometrical structure of the surrounding environment. This problem statement was motivated by the GPS-denied scenario for a sea-surface vehicle developed at Plymouth University named Springer. The algorithms proposed in this thesis are mainly adapted for the Springer’s environmental conditions, so that the vehicle can navigate on a vision based localization system when GPS is not available; such environments include estuarine areas, forests and the occasional semi-urban territories. The research objectives are constrained versions of the ever-abiding problems in the fields of multiple view geometry and mobile robotics. The research is proposing new techniques or improving existing ones for problems such as scene reconstruction, relative camera pose recovery and filtering, always in the context of the aforementioned landscapes (i.e., rivers, forests, etc.). Although visual tracking is paramount for the generation of data point correspondences, this thesis focuses primarily on the geometric aspect of the problem as well as with the probabilistic framework in which the optimization of pose and structure estimates takes place. Besides algorithms, the deliverables of this research should include the respective implementations and test data for these algorithms in the form of a software library and a dataset containing footage of estuarine regions taken from a boat, along with synchronized sensor logs. This thesis is not the final analysis on vision based navigation. It merely proposes various solutions for the localization problem of a vehicle navigating in natural environments either on land or on the surface of the water. Although these solutions can be used to provide position and orientation estimates when GPS is not available, they have limitations and there is still a vast new world of ideas to be explored.

en_US
dc.description.sponsorshipUTC Aerospace Systemsen_US
dc.language.isoenen_US
dc.publisherPlymouth Universityen_US
dc.subjectVisual SLAMen_US
dc.subjectMultiple View Geometryen_US
dc.subjectAutonomous Vehicleen_US
dc.subjectRoboticsen_US
dc.subjectSea Surface Vehicleen_US
dc.subject3D Computer Visionen_US
dc.subjectVisual Odometryen_US
dc.subjectMobile Roboticsen_US
dc.subjectSLAMen_US
dc.subject.classificationPhDen_US
dc.titleVisual Odometry and Mapping in Natural Environments for Arbitrary Camera Motion Modelsen_US
dc.typeThesis
plymouth.versionpublishableen_US
dc.identifier.doihttp://dx.doi.org/10.24382/3764
dc.identifier.doihttp://dx.doi.org/10.24382/3764
dc.rights.embargoperiodNo embargoen_US
rioxxterms.funderNot availableen_US
rioxxterms.identifier.projectNot availableen_US


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