Multi-modal 3D Polygon Maps for Semantic Mapping

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dc.creatorWiemann, Thomas-
dc.date.accessioned2020-10-26T13:58:42Z-
dc.date.available2020-10-26T13:58:42Z-
dc.date.issued2020-10-26T13:58:42Z-
dc.identifier.citationHabilitationsschrift Universität Osnabrück, Fachbereich 6 - Mathematik/Informatik, Osnabrück, 2020ger
dc.identifier.urihttps://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-202010263636-
dc.description.abstractEnabling intelligent mobile systems to interact with their surroundings requires a suitable environment model that incorporates different layers of information consistently. This model is the decision base for all planned and executed actions. Such models typically include a geometric map, i.e., a representation that encodes geometric information together with features that can be detected with the system's sensors, as well conceptual and factual background knowledge about the application domain. The challenge in creating such semantic maps is to find representations that consistently fuse different information layers in a memory efficient way, are scalable in terms of mapped area, flexible in terms of the application domain and can be delivered on demand from a dedicated storage device. This thesis summarizes contributions to three different aspects of semantic mapping, namely the creation of annotated multi-modal polygonal maps of large scale environments, means to distribute and manage geometric and semantic knowledge, and examples of successful real world applications of the latter.eng
dc.rightsAttribution-NoDerivs 3.0 Germany*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/de/*
dc.subjectSemantic Mappingeng
dc.subjectSensor Data Fusioneng
dc.subjectSLAMeng
dc.subjectSurface Reconstructioneng
dc.subjectLocalizationeng
dc.subjectKnowledge Representationeng
dc.subject.ddc004 - Informatikger
dc.titleMulti-modal 3D Polygon Maps for Semantic Mappingeng
dc.typeBuch [book]ger
thesis.locationOsnabrückger
thesis.institutionUniversitätger
thesis.typeHabilitation [thesis.habilitation]ger
thesis.date2020-10-01-
orcid.creatorhttps://orcid.org/0000-0003-0710-872X-
dc.subject.bk54.72 - Künstliche Intelligenzger
dc.subject.ccsI.2.9 - Roboticsger
Enthalten in den Sammlungen:FB06 - Hochschulschriften

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