A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance

The increasing demand for agricultural products and rising production costs have intensified labour shortages in the agricultural sector. Manual harvesting remains essential for products with specific designations, such as wine grapes, where automated solutions cannot match human operators’ dexterit...

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Autores: Conejero Rodríguez, María Nuria, Montes, Héctor, Bengochea-Guevara, José M., Garrido-Rey, Laura, Andújar, Dionisio, Ribeiro Seijas, Ángela
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/402699
Acceso en línea:http://hdl.handle.net/10261/402699
https://api.elsevier.com/content/abstract/scopus_id/105002241906
Access Level:acceso abierto
Palabra clave:Collaborative robotics
Manual harvesting
Robotic fleet
Transport robot
Yield map
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spelling A collaborative robotic fleet for yield mapping and manual fruit harvesting assistanceConejero Rodríguez, María NuriaMontes, HéctorBengochea-Guevara, José M.Garrido-Rey, LauraAndújar, DionisioRibeiro Seijas, ÁngelaCollaborative roboticsManual harvestingRobotic fleetTransport robotYield mapThe increasing demand for agricultural products and rising production costs have intensified labour shortages in the agricultural sector. Manual harvesting remains essential for products with specific designations, such as wine grapes, where automated solutions cannot match human operators’ dexterity, speed, and care. Minimizing transportation time is also crucial for preserving produce quality and optimizing efficiency. This study aims to optimize harvesting efficiency and vineyard management through the design and implementation of a mobile robotic platform. The platform combines operator dexterity with robotic assistance, continuously tracking operators as they deposit harvested grapes into a harvesting box carried by a robot while gathering data for yield map development. Adaptable to various manual fruit-picking processes, the platform can be integrated into a collaborative harvesting assistance fleet. Field experiments conducted at the Bodegas Terras Gauda (UTM coordinates: 41.95, −8.80, O Rosal, Pontevedra, Spain) vineyard, indicated that operators using robotic assistance reduced their average harvesting time per box by 6 min, increased their total harvested yield by 72.50 kg after two hours (up to 50% more), and reduced manual labour costs by 22.50%. A yield map was developed with high-accuracy GNSS data and an industrial scale mounted on the robot. The map geolocates the weights collected with a maximum variability error of 0.11 kg and successfully expresses grapevine density variability within the same vineyard row. The system preserves produce quality during transportation and significantly eliminates physical strain among operators. These results demonstrate the potential of the robotic platform to improve the efficiency of manual harvesting while maintaining high-quality outcomes.This paper was carried out within the framework of the FlexiGroBots project funded by the European Union under the H2020 Program with Grant Agreement Id. 101017111. The authors acknowledge valuable help and contributions from Bodegas Terras Gauda, S.A. for generously providing the land to conduct the experiments and all partners of the project. All authors have reviewed and approved the final manuscript.Peer reviewedElsevier BVEuropean CommissionBodega Terras GaudaConejero Rodríguez, María Nuria [0000-0002-9372-3739]Montes, Héctor [0000-0001-8638-9966]Bengochea-Guevara, José M. [0000-0003-4081-7325]Andújar, Dionisio [0000-0002-5801-0944]Ribeiro, Angela [0000-0001-5807-8132]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/402699https://api.elsevier.com/content/abstract/scopus_id/105002241906reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/101017111The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.compag.2025.110351https://doi.org/10.1016/j.compag.2025.110351Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4026992026-05-22T06:33:51Z
dc.title.none.fl_str_mv A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
title A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
spellingShingle A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
Conejero Rodríguez, María Nuria
Collaborative robotics
Manual harvesting
Robotic fleet
Transport robot
Yield map
title_short A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
title_full A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
title_fullStr A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
title_full_unstemmed A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
title_sort A collaborative robotic fleet for yield mapping and manual fruit harvesting assistance
dc.creator.none.fl_str_mv Conejero Rodríguez, María Nuria
Montes, Héctor
Bengochea-Guevara, José M.
Garrido-Rey, Laura
Andújar, Dionisio
Ribeiro Seijas, Ángela
author Conejero Rodríguez, María Nuria
author_facet Conejero Rodríguez, María Nuria
Montes, Héctor
Bengochea-Guevara, José M.
Garrido-Rey, Laura
Andújar, Dionisio
Ribeiro Seijas, Ángela
author_role author
author2 Montes, Héctor
Bengochea-Guevara, José M.
Garrido-Rey, Laura
Andújar, Dionisio
Ribeiro Seijas, Ángela
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Bodega Terras Gauda
Conejero Rodríguez, María Nuria [0000-0002-9372-3739]
Montes, Héctor [0000-0001-8638-9966]
Bengochea-Guevara, José M. [0000-0003-4081-7325]
Andújar, Dionisio [0000-0002-5801-0944]
Ribeiro, Angela [0000-0001-5807-8132]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Collaborative robotics
Manual harvesting
Robotic fleet
Transport robot
Yield map
topic Collaborative robotics
Manual harvesting
Robotic fleet
Transport robot
Yield map
description The increasing demand for agricultural products and rising production costs have intensified labour shortages in the agricultural sector. Manual harvesting remains essential for products with specific designations, such as wine grapes, where automated solutions cannot match human operators’ dexterity, speed, and care. Minimizing transportation time is also crucial for preserving produce quality and optimizing efficiency. This study aims to optimize harvesting efficiency and vineyard management through the design and implementation of a mobile robotic platform. The platform combines operator dexterity with robotic assistance, continuously tracking operators as they deposit harvested grapes into a harvesting box carried by a robot while gathering data for yield map development. Adaptable to various manual fruit-picking processes, the platform can be integrated into a collaborative harvesting assistance fleet. Field experiments conducted at the Bodegas Terras Gauda (UTM coordinates: 41.95, −8.80, O Rosal, Pontevedra, Spain) vineyard, indicated that operators using robotic assistance reduced their average harvesting time per box by 6 min, increased their total harvested yield by 72.50 kg after two hours (up to 50% more), and reduced manual labour costs by 22.50%. A yield map was developed with high-accuracy GNSS data and an industrial scale mounted on the robot. The map geolocates the weights collected with a maximum variability error of 0.11 kg and successfully expresses grapevine density variability within the same vineyard row. The system preserves produce quality during transportation and significantly eliminates physical strain among operators. These results demonstrate the potential of the robotic platform to improve the efficiency of manual harvesting while maintaining high-quality outcomes.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/402699
https://api.elsevier.com/content/abstract/scopus_id/105002241906
url http://hdl.handle.net/10261/402699
https://api.elsevier.com/content/abstract/scopus_id/105002241906
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/101017111
The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.compag.2025.110351
https://doi.org/10.1016/j.compag.2025.110351
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier BV
publisher.none.fl_str_mv Elsevier BV
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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