A modular control architecture for safe and robust robot operation and inspection in steep slope vineyards
Zusammenfassung
In fall line cultivation of vineyards, the vines are planted vertically to the hill's slope. Therefore, steep slope vineyards require a high amount of manual labor, doubling production costs. Working in such environments is exhausting and laborious. Therefore, autonomous robots should assist humans in reducing costs and increasing safety. However, current state-of-the-art robotic systems and control architectures are not designed to work in such harsh environments with extreme terrains. Therefore, this work proposes and modular control architecture for safe and robust autonomous working in steep slope environments. Tests in an authentic vineyard near the Moselle river in Germany prove the approach's feasibility and robustness.
- Vollständige Referenz
- BibTeX
Gassen, Ei., Wolf, Pa. & Berns, Ka.,
(2022).
A modular control architecture for safe and robust robot operation and inspection in steep slope vineyards.
In:
Demmler, D., Krupka, D. & Federrath, H.
(Hrsg.),
INFORMATIK 2022.
Gesellschaft für Informatik, Bonn.
(S. 947-959).
DOI: 10.18420/inf2022_80
@inproceedings{mci/Gassen2022,
author = {Gassen,Eike AND Wolf,Patrick AND Berns,Karsten},
title = {A modular control architecture for safe and robust robot operation and inspection in steep slope vineyards},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 947-959 } ,
doi = { 10.18420/inf2022_80 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Gassen,Eike AND Wolf,Patrick AND Berns,Karsten},
title = {A modular control architecture for safe and robust robot operation and inspection in steep slope vineyards},
booktitle = {INFORMATIK 2022},
year = {2022},
editor = {Demmler, Daniel AND Krupka, Daniel AND Federrath, Hannes} ,
pages = { 947-959 } ,
doi = { 10.18420/inf2022_80 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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|---|---|---|---|---|
| rsflab_03.pdf | 4.957Mb | Öffnen |
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Mehr Information
DOI: 10.18420/inf2022_80
ISBN: 978-3-88579-720-3
ISSN: 1617-5468
Datum: 2022
Sprache:
(en)
(en)
