Verlagslink: https://www.scitepress.org/Papers/2022/113213/113213.pdf
Verlagslink DOI: 10.5220/0011321300003271
Titel: Challenges of autonomous in-field fruit harvesting and concept of a robotic solution
Sprache: Englisch
Autorenschaft: Tiedemann, Tim 
Cordes, Florian 
Keppner, Matthis 
Peters, Heiner 
Herausgeber*In: Gini, Giuseppina 
Nijmeijer, Henk 
Burgard, Wolfram 
Filev, Dimitar 
Schlagwörter: Agricultural Robotics; Machine Learning; Autonomous Harvesting; Multi-spectral Imaging; Classification
Erscheinungsdatum: 2022
Verlag: SciTePress
Teil der Schriftenreihe: Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2022) 
Bandangabe: 1
Anfangsseite: 508
Endseite: 515
Projekt: Robotik in der Landwirtschaft 
Konferenz: International Conference on Informatics in Control, Automation and Robotics 2022 
Zusammenfassung: 
Since the beginning of humans cultivating plants in fields, agriculture underwent a continuous shift from purely manual labor over simple machinery to more and more automated processes. Autonomous driving with navigation and self localization in the field is state of the art. Also, automated machines for fruit processing are available as well. In cases where the fruit is damageable and varies in size and shape, automated processing is challenging. One example of such damageable fruits are strawberries. Size, weight, and shape at the optimal ripeness can vary a lot. Additionally, a change from ripe to overripe occurs relatively quick and is sometimes hard to recognize. A further challenge when harvesting strawberries is a dense leafage that can cover the fruits partly or completely. In this paper, a concept of an autonomous in-field strawberry harvesting robot for non-elevated but ground-raised strawberry plants, with or without a tunnel, is presented. The robot is supposed to use mul ti-spectral imaging and machine learning based ripeness classification. Besides the overall concept, first data of this early-stage project is shown, too.
URI: http://hdl.handle.net/20.500.12738/13236
ISBN: 978-989-758-585-2
ISSN: 2184-2809
Einrichtung: Forschungs- und Transferzentrum Smart Systems 
Department Informatik 
Fakultät Technik und Informatik 
Dokumenttyp: Konferenzveröffentlichung
Sponsor / Fördernde Einrichtung: Bundesministerium für Ernährung und Landwirtschaft 
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