Lakshadeep Naik

Lakshadeep Naik

PhD candidate at University of Southern Denmark (SDU)

Semantic mapping extension for OpenStreetMap applied to indoor robot navigation

URL: https://ieeexplore.ieee.org/abstract/document/8793641

Abstract: 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 are introduced for basic indoor structures such as walls, doors, corridors, elevators, etc. 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 advantage of the proposed graph-based map representation is that it allows 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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Recommended citation: Naik, L., Blumenthal, S., Huebel, N., Bruyninckx, H., & Prassler, E. (2019, May). Semantic mapping extension for OpenStreetMap applied to indoor robot navigation. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 3839-3845). IEEE.