A systematic analysis of scan matching techniques for localization in dense orchards

In recent years, different methods have been studied to determine machinery position within a grove, as an alternative for complementing GNSS (global navigation satellite system) information in cases where GNSS signal is occluded. Such a situation can be observed when agricultural machinery travels...

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Detalhes bibliográficos
Autores: Guevara, Javier, Gené Mola, Jordi, Gregorio López, Eduard, Auat Cheein, Fernando
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/466828
Acesso em linha:https://doi.org/10.1016/j.atech.2024.100607
https://hdl.handle.net/10459.1/466828
Access Level:acceso abierto
Palavra-chave:Global positioning system
Point cloud registration
Mobile sensing
Vehicle localization
Phenotyping
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spelling A systematic analysis of scan matching techniques for localization in dense orchardsGuevara, JavierGené Mola, JordiGregorio López, EduardAuat Cheein, FernandoGlobal positioning systemPoint cloud registrationMobile sensingVehicle localizationPhenotypingIn recent years, different methods have been studied to determine machinery position within a grove, as an alternative for complementing GNSS (global navigation satellite system) information in cases where GNSS signal is occluded. Such a situation can be observed when agricultural machinery travels under dense foliage or on the slopes of mountains. Scan matching techniques arise as a possible solution for localizing the machinery, complementing the absence of the GNSS signal when necessary. However, since key points are difficult to obtain in heterogeneous, unstructured and non-rigid environments (such as orchard plants), the performance of scan matching techniques often decreases in agricultural environments. This paper suggests dividing the point clouds into horizontal and vertical segments to improve the performance of scan-matching methods in orchards. It also examines the best way for registered frames to overlap. We validate the analysis with extensive experimentation in a Fuji apple orchard. The results show that the cumulative localization error in scan matching techniques can be notoriously decreased with selective parts of the orchard, by up to 60%. The experimentation performed herein suggests that the proposed methodology can complement the GNSS navigation in a middle-long path.This work was partly funded by ANID FB0008, PIIC 030/2018 DGIIP-UTFSM Chile, the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). This work is also part of the DIGIFRUIT project (grant TED2021-131871B-I00) funded by MICIU/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. The Spanish Ministry of Education is thanked for Mr. J. Gené's pre-doctoral fellowships (FPU15/03355).Elsevier2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1016/j.atech.2024.100607https://hdl.handle.net/10459.1/466828reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00Reproducció del document publicat a: https://doi.org/10.1016/j.atech.2024.100607Smart Agricultural Technology, 2024, vol. 9 (2024), num. 100607cc-by-nc-nd, (c) Guevara et al., 2024info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/deedoai:recercat.cat:10459.1/4668282026-05-29T05:05:01Z
dc.title.none.fl_str_mv A systematic analysis of scan matching techniques for localization in dense orchards
title A systematic analysis of scan matching techniques for localization in dense orchards
spellingShingle A systematic analysis of scan matching techniques for localization in dense orchards
Guevara, Javier
Global positioning system
Point cloud registration
Mobile sensing
Vehicle localization
Phenotyping
title_short A systematic analysis of scan matching techniques for localization in dense orchards
title_full A systematic analysis of scan matching techniques for localization in dense orchards
title_fullStr A systematic analysis of scan matching techniques for localization in dense orchards
title_full_unstemmed A systematic analysis of scan matching techniques for localization in dense orchards
title_sort A systematic analysis of scan matching techniques for localization in dense orchards
dc.creator.none.fl_str_mv Guevara, Javier
Gené Mola, Jordi
Gregorio López, Eduard
Auat Cheein, Fernando
author Guevara, Javier
author_facet Guevara, Javier
Gené Mola, Jordi
Gregorio López, Eduard
Auat Cheein, Fernando
author_role author
author2 Gené Mola, Jordi
Gregorio López, Eduard
Auat Cheein, Fernando
author2_role author
author
author
dc.subject.none.fl_str_mv Global positioning system
Point cloud registration
Mobile sensing
Vehicle localization
Phenotyping
topic Global positioning system
Point cloud registration
Mobile sensing
Vehicle localization
Phenotyping
description In recent years, different methods have been studied to determine machinery position within a grove, as an alternative for complementing GNSS (global navigation satellite system) information in cases where GNSS signal is occluded. Such a situation can be observed when agricultural machinery travels under dense foliage or on the slopes of mountains. Scan matching techniques arise as a possible solution for localizing the machinery, complementing the absence of the GNSS signal when necessary. However, since key points are difficult to obtain in heterogeneous, unstructured and non-rigid environments (such as orchard plants), the performance of scan matching techniques often decreases in agricultural environments. This paper suggests dividing the point clouds into horizontal and vertical segments to improve the performance of scan-matching methods in orchards. It also examines the best way for registered frames to overlap. We validate the analysis with extensive experimentation in a Fuji apple orchard. The results show that the cumulative localization error in scan matching techniques can be notoriously decreased with selective parts of the orchard, by up to 60%. The experimentation performed herein suggests that the proposed methodology can complement the GNSS navigation in a middle-long path.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.atech.2024.100607
https://hdl.handle.net/10459.1/466828
url https://doi.org/10.1016/j.atech.2024.100607
https://hdl.handle.net/10459.1/466828
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00
Reproducció del document publicat a: https://doi.org/10.1016/j.atech.2024.100607
Smart Agricultural Technology, 2024, vol. 9 (2024), num. 100607
dc.rights.none.fl_str_mv cc-by-nc-nd, (c) Guevara et al., 2024
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/4.0/deed
rights_invalid_str_mv cc-by-nc-nd, (c) Guevara et al., 2024
https://creativecommons.org/licenses/by-nc-nd/4.0/deed
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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