Publisher URL: https://www.scitepress.org/Papers/2022/113213/113213.pdf
Publisher DOI: 10.5220/0011321300003271
Title: Challenges of autonomous in-field fruit harvesting and concept of a robotic solution
Language: English
Authors: Tiedemann, Tim 
Cordes, Florian 
Keppner, Matthis 
Peters, Heiner 
Editor: Gini, Giuseppina 
Nijmeijer, Henk 
Burgard, Wolfram 
Filev, Dimitar 
Keywords: Agricultural Robotics;Machine Learning;Autonomous Harvesting;Multi-spectral Imaging;Classification
Issue Date: 2022
Publisher: SciTePress
Part of Series: Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2022) 
Volume number: 1
Startpage: 508
Endpage: 515
Project: Robotik in der Landwirtschaft 
Conference: International Conference on Informatics in Control, Automation and Robotics 2022 
Abstract: 
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
Institute: Forschungs- und Transferzentrum Smart Systems 
Department Informatik 
Fakultät Technik und Informatik 
Type: Chapter/Article (Proceedings)
Funded by: Bundesministerium für Ernährung und Landwirtschaft 
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