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Rotation and Translation Invariant 3D Descriptor for Surfaces

: Hampp, Joshua; Bormann, Richard

Postprint urn:nbn:de:0011-n-3664892 (2.6 MByte PDF)
MD5 Fingerprint: 4d49858103d2c8685c6d2b18c0af0ba2
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Created on: 2.12.2015

Zhang, J. (General Chair) ; IEEE Robotics and Automation Society; IEEE Industrial Electronics Society:
IROS 2015, IEEE/RSJ International Conference on Intelligent Robots and Systems : Hamburg, Germany, 28 September - 2 October 2015
Piscataway, NJ, USA: IEEE Press, 2015
ISBN: 978-1-4799-9993-4 (USB)
ISBN: 978-1-4799-9994-1 (print)
ISBN: 978-1-4799-9995-8
International Conference on Intelligent Robots and Systems (IROS) <2015, Hamburg>
Conference Paper, Electronic Publication
Fraunhofer IPA ()
Robotersteuerung; Invarianz; Mobiler Roboter; Mobiler Notfallassistent (MobiNa); Rotation Invariance; Lokalisation; Notfallerkennung

We present a descriptor estimator for surface-based 3D input data for coarse localization of mobile robots. From the input pointclouds surfaces are reconstructed and simplified to detect stable keypoints which are used to evaluate rotation and translation invariant features. The invariance is achieved by transforming the triangulated input data into the frequency domain by Fourier transformation and spherical harmonics. The pipeline was evaluated against state of the art algorithms and tested to localize a mobile robot. The source code is publicly available.