Spatio-Temporal Terrain Classification for Mapping and Robot Localization

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dc.contributor.advisor Zell, Andreas (Prof. Dr.)
dc.contributor.author Laible, Stefan
dc.date.accessioned 2017-04-04T08:26:00Z
dc.date.available 2017-04-04T08:26:00Z
dc.date.issued 2017-04-04
dc.identifier.other 486273555 de_DE
dc.identifier.uri http://hdl.handle.net/10900/75701
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-757010 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-17103
dc.description.abstract Detection and classification of the surrounding terrain is a fundamental ability of a mobile robot in outdoor navigation to enable safe and efficient path planning. Our robot is equipped with a 3D LiDAR and a color camera, since these sensors complement each other very well. The terrain in front of the robot is divided into a grid, and each grid cell is classified individually using the sensor measurements. A new method for 3D LiDAR-based terrain classification with easy-to-compute and yet discriminative 3D features based on intensity and roughness histograms is presented. To exploit the fact that terrain appears in contiguous areas, spatial dependencies between the individual cells of the terrain grid are taken into account by modeling the grid as a Conditional random field. As the robot moves, we constantly update a terrain map with the current classification result. In this way, we are not only able to exploit temporal dependencies, but we are building whole terrain maps of the environment. Finally, we show how to use these maps for a semantic localization of the robot. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.classification Robotik , Maschinelles Lernen de_DE
dc.subject.ddc 004 de_DE
dc.subject.other terrain classification en
dc.subject.other terrain mapping en
dc.subject.other spatio-temporal classification en
dc.subject.other semantic localization en
dc.subject.other robot localization en
dc.subject.other mobile robotics en
dc.subject.other outdoor robotics en
dc.subject.other 3D LiDAR en
dc.title Spatio-Temporal Terrain Classification for Mapping and Robot Localization en
dc.type PhDThesis de_DE
dcterms.dateAccepted 2017-01-19
utue.publikation.fachbereich Informatik de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE

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