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Semantic mapping extension for OpenStreetMap applied to indoor robot navigation

  • In this work a graph-based, semantic mapping approach for indoor robotics applications is presented, which is extending OpenStreetMap (OSM) with robotic-specific, semantic, topological, and geometrical information. Models for common indoor structures (such as walls, doors, corridors, elevators, etc.) are introduced. The architectural principles support composition with additional domain and application specific knowledge. As an example, a model for an area is introduced and it is explained how this can be used in navigation. A key advantages of the proposed graph-based map representation is that it allows seamless transitions between maps, e.g., indoor and outdoor maps by exploiting the hierarchical structure of the graphs. Finally, the compatibility of the approach with existing, grid-based motion planning algorithms is shown.

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Document Type:Conference Object
Author:Lakshadeep Naik, Sebastian Blumenthal, Nico Huebel, Herman Bruyninckx, Erwin Prassler
Parent Title (English):IEEE International Conference on Robotics and Automation 2019 (ICRA 2019), Montreal, QC, Canada, 20-24 May 2019
Date of first publication:2019/08/12
This work was supported by the European Union’s Horizon 2020 projects ROPOD (grant agreement No 731848) and RobMoSys (grant agreement No 732410).
Departments, institutes and facilities:Fachbereich Informatik
Projects:ROPOD - Ultra-flat, ultra-flexible, cost-effective robotic pods for handling legacy in logistics (EC/H2020/731848)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2019/01/29