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3D mapping for multi hybrid robot cooperation

: Surmann, H.; Berninger, N.; Worst, R.

Postprint urn:nbn:de:0011-n-4803454 (5.0 MByte PDF)
MD5 Fingerprint: 61b1bc0c05b3af4bd0cf74ea479f8072
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Created on: 24.1.2018

Institute of Electrical and Electronics Engineers -IEEE-:
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 : Vancouver, BC, Canada, September 24 - 28, 2017
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-2682-5 (electronic)
ISBN: 978-1-5386-2681-8 (USB)
ISBN: 978-1-5386-2683-2 (print on demand)
International Conference on Intelligent Robots and Systems (IROS) <2017, Vancouver>
European Commission EC
FP7-ICT; 609763; TRADR
Conference Paper, Electronic Publication
Fraunhofer IAIS ()
camera; image reconstruction; lasers; real-time system; robot sensing system; three-dimensional displays

This paper presents a novel approach to build consistent 3D maps for multi robot cooperation in USAR environments. The sensor streams from unmanned aerial vehicles (UAVs) and ground robots (UGV) are fused in one consistent map. The UAV camera data are used to generate 3D point clouds that are fused with the 3D point clouds generated by a rolling 2D laser scanner at the UGV. The registration method is based on the matching of corresponding planar segments that are extracted from the point clouds. Based on the registration, an approach for a globally optimized localization is presented. Apart from the structural information of the point clouds, it is important to mention that no further information is required for the localization. Two examples show the performance of the overall registrat ion