TY  - CONF
A1  - Surmann, Hartmut
A1  - Berninger, Nils
A1  - Worst, Rainer
A2  - IEEE/RSJ International Conference on Intelligent Robots and Systems <2017, Vancouver, British Columbia>, 
A2  - Corporation Institute of Electrical and Electronics Engineers, 
T1  - 3D mapping for multi hybrid robot cooperation
T2  - IROS Vancouver 2017. IEEE/RSJ International Conference on Intelligent Robots and Systems, Vancouver, BC, Canada September 24-28, 2018. Conference digest
N2  - 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 registration.
Y1  - 2017
UR  - https://whge.opus.hbz-nrw.de/frontdoor/index/index/docId/3123
SN  - 978-1-5386-2682-5
SP  - 626
EP  - 633
PB  - IEEE
CY  - [Piscataway, NJ]
ER  -