Part of the book series:Informatik aktuell ((INFORMAT))
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Abstract
This paper describes an absolute localisation method for an unmanned ground vehicle (UGV) if GPS is unavailable for the vehicle. The basic idea is to combine an unmanned aerial vehicle (UAV) to the ground vehicle and use it as an external sensor platform to achieve an absolute localisation of the robotic team. Beside the discussion of the rather naive method directly using the GPS position of the aerial robot to deduce the ground robot’s position the main focus of this paper lies on the indirect usage of the telemetry data of the aerial robot combined with live video images of an onboard camera to realise a registration of local video images with apriori registered orthophotos. This yields to a precise driftless absolute localisation of the unmanned ground vehicle. Experiments with our robotic team (AMOR and PSYCHE) successfully verify this approach.
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Authors and Affiliations
Institute for Real-Time Learning Systems, University of Siegen, FB 12 — Electrical Engineering and Computer Science, Hölderlinstr. 3, 57068, Siegen
Lars Kuhnert, Markus Ax, Matthias Langer, Duong Nguyen Van & Klaus-Dieter Kuhnert
- Lars Kuhnert
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- Markus Ax
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- Matthias Langer
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- Duong Nguyen Van
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- Klaus-Dieter Kuhnert
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Editors and Affiliations
Institut für Anthropomatik, Karlsruher Institut für Technologie - KIT, Adenauerring 4, 76131, Karlsruhe
Rüdiger Dillmann & Tobias Gindele &
Lehrstuhl für Interaktive Echtzeitsysteme Fraunhofer-Institut für Informations- und Datenverarbeitung IITB, Karlsruher Institut für Technologie, Fraunhoferstr. 1, 76131, Karlsruhe
Jürgen Beyerer
Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie, Engler-Bunte-Ring 21, 76131, Karlsruhe
Christoph Stiller
FZI Forschungszentrum Informatik, Technisch kognitive Assistenzsysteme, Haid-und-Neu-Str. 10-14, 76131, Karlsruhe
J. Marius Zöllner
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Kuhnert, L., Ax, M., Langer, M., Nguyen Van, D., Kuhnert, KD. (2009). Absolute High-Precision Localisation of an Unmanned Ground Vehicle by Using Real-Time Aerial Video Imagery for Geo-referenced Orthophoto Registration. In: Dillmann, R., Beyerer, J., Stiller, C., Zöllner, J.M., Gindele, T. (eds) Autonome Mobile Systeme 2009. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10284-4_19
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