Multi-modal 3D Polygon Maps for Semantic Mapping

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Title: Multi-modal 3D Polygon Maps for Semantic Mapping
Authors: Wiemann, Thomas
ORCID of the author: https://orcid.org/0000-0003-0710-872X
Abstract: Enabling 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.
Citations: Habilitationsschrift Universität Osnabrück, Fachbereich 6 - Mathematik/Informatik, Osnabrück, 2020
URL: https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-202010263636
Subject Keywords: Semantic Mapping; Sensor Data Fusion; SLAM; Surface Reconstruction; Localization; Knowledge Representation
Issue Date: 26-Oct-2020
License name: Attribution-NoDerivs 3.0 Germany
License url: http://creativecommons.org/licenses/by-nd/3.0/de/
Type of publication: Buch [book]
Appears in Collections:FB06 - Hochschulschriften

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