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Authors: Christian Hofmann ; Mathias Fichtner ; Markus Lieret and Jörg Franke

Affiliation: Institute for Factory Automation and Production Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Egerlandstr. 7-9, 91058 Erlangen, Germany

Keyword(s): UAV, Semantic Mapping, Object Detection, Information Fusion.

Abstract: Unmanned Aerial Vehicles (UAVs) are required to fulfill more and more complex tasks in indoor environments like inspection, stock-taking or transportation of goods. For these tasks, they need to percept objects and obstacles in the environment, navigate safely in it and sometimes even interact with it. A step towards generating a comprehensive environmental overview for robots are semantic maps. Nevertheless, UAVs have several constraints concerning size, weight and power consumption and thus computational resources. In this paper an efficient object-oriented semantic mapping approach suitable for UAVs and similar constrained robots in dynamic environments is proposed. The approach can be completely executed on a computer suited as onboard computer of an UAV. A map comprising semantic information and dynamic objects is generated and updated with update rate of more than 10 Hz.

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Paper citation in several formats:
Hofmann, C.; Fichtner, M.; Lieret, M. and Franke, J. (2022). Efficient Semantic Mapping in Dynamic Environments. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 803-810. DOI: 10.5220/0010770200003124

@conference{visapp22,
author={Christian Hofmann. and Mathias Fichtner. and Markus Lieret. and Jörg Franke.},
title={Efficient Semantic Mapping in Dynamic Environments},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={803-810},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010770200003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Efficient Semantic Mapping in Dynamic Environments
SN - 978-989-758-555-5
IS - 2184-4321
AU - Hofmann, C.
AU - Fichtner, M.
AU - Lieret, M.
AU - Franke, J.
PY - 2022
SP - 803
EP - 810
DO - 10.5220/0010770200003124
PB - SciTePress

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