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Titel:

Road Geometry Estimation for Urban Semantic Maps using Open Data

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Landsiedel, Christian; Wollherr, Dirk
Abstract:
Complex robotic tasks require the use of knowledge that cannot be acquired with the sensor repertoire of a mobile, autonomous robot alone. For robots navigating in urban environments, geospatial open data repositories such as OpenStreetMap (OSM) provide a source for such knowledge. We propose the integration of a 3D metric environment representation with the semantic knowledge from such a database. The application we describe uses street network information from OSM to improve street geometry in...     »
Stichworte:
Spatial reasoning, hybrid maps, scene understanding
Zeitschriftentitel:
Advanced Robotics
Jahr:
2017
Jahr / Monat:
2017-03
Monat:
Mar
Seitenangaben Beitrag:
1-9
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1080/01691864.2016.1250675
WWW:
http://dx.doi.org/10.1080/01691864.2016.1250675
Verlag / Institution:
Taylor & Francis
Publikationsdatum:
02.11.2016
Semester:
WS 16-17
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