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A modular hybrid localization approach for mobile robots combining local grid maps and natural landmarks

 
: Mirus, Florian; Garcia Lopez, Felipe; Slomian, Frank; Gruhler, Matthias; Dörr, Stefan; Pfadt, Jürgen

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Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Applied Computing -SIGAPP-:
31st ACM/SIGAPP Symposium on Applied Computing, SAC 2016. Proceedings : April 4-8, 2016, Pisa, Italy
New York: ACM, 2016
ISBN: 978-1-4503-3739-7
pp.287-290
Symposium on Applied Computing (SAC) <31, 2016, Pisa>
English
Conference Paper
Fraunhofer IPA ()
mobile robot; Lokalisierung; Robotertechnik; navigation; Sensorik; Kalman-Filter

Abstract
This paper presents a hybrid localization approach for mobile robots combining local grid maps and natural landmarks. The approach at hand benefits from the advantages of both environment representations. While using memory-efficient geometric models describing natural landmarks as features for localization in structured regions, the proposed system clusters the remaining areas as raw local grid maps and incorporates those as pose features only for unstructured areas of the environment. To evaluate the functionality and performance of the approach at hand, extensive testing and benchmarking in an experimental setup has been conducted using an external sensor system for reference measurements.

: http://publica.fraunhofer.de/documents/N-393701.html