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3D SLAM with scan matching and factor graph optimization

 
: Emter, Thomas; Petereit, Janko

:
Postprint urn:nbn:de:0011-n-5314982 (3.4 MByte PDF)
MD5 Fingerprint: b5f486c16b1091ff374084bb34689f43
Erstellt am: 26.3.2019


Informationstechnische Gesellschaft -ITG-; Verband Deutscher Maschinen- und Anlagenbau e.V. -VDMA-, Frankfurt/Main; Informationskreis für Raumplanung e.V. -IfR-, Dortmund:
50th International Symposium on Robotics, ISR 2018 : June 20-21, 2018 Messe München, Entrance East, Munich, Germany
Berlin: VDE Verlag, 2018
ISBN: 978-3-8007-4699-6
ISBN: 3-8007-4699-9
S.292-299
International Symposium on Robotics (ISR) <50, 2018, Munich>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
For autonomous navigation, a mobile robot needs the capability to estimate its pose while simultaneously mapping its environment. This contribution presents an approach for fusing data from multiple asynchronous sensors using factor graphs. Full 3D SLAM is performed on data from several localization sensors and point clouds from a 3D LiDAR. The scans from the LiDAR are integrated by scan matching for relative motion estimation and are also used for loop closure.

: http://publica.fraunhofer.de/dokumente/N-531498.html