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Authordc.contributor.authorTampier Cotoras, Carlos Andrés
Authordc.contributor.authorMascaró, Mauricio
Authordc.contributor.authorRuiz del Solar San Martín, Javier
Admission datedc.date.accessioned2022-06-28T20:12:36Z
Available datedc.date.available2022-06-28T20:12:36Z
Publication datedc.date.issued2021
Cita de ítemdc.identifier.citationAppl. Sci. 2021, 11, 8718.es_ES
Identifierdc.identifier.other10.3390/app11188718
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/186296
Abstractdc.description.abstractThis paper describes an autonomous loading system for load-haul-dump (LHD) machines used in underground mining. The loading of fragmented rocks from draw points is a complex task due to many factors including: bucket-rock interaction forces that are difficult to model, humidity that increases cohesion forces, and the possible presence of boulders. The proposed system is designed to integrate all the relevant tasks required for ore loading: rock pile identification, LHD positioning in front of the ore pile, charging and excavating into the ore pile, pull back and payload weighing. The system follows the shared autonomy paradigm: given that the loading process may not be completed autonomously in some cases, it takes into account that the machine/agent can detect this situation and ask a human operator for assistance. The most novel component of the proposed autonomous loading system is the excavation algorithm, and the disclosure of the results obtained from its application in a real underground production environment. The excavation method is based on the way that human operators excavate: while excavating, the bucket is tilted intermittently in order to penetrate the material, and the boom of the LHD is lifted on demand to prevent or correct wheel skidding. Wheel skidding is detected with a patented method that uses LIDAR-based odometry and internal measurements of the LHD. While a complete loading system was designed, the validation had to be divided in two stages. One stage included the rock pile identification and positioning, and the other included the charging, excavation, pull back, and weighting processes. The stage concerning the excavation algorithm was validated using full-scale experiments with a real-size LHD in an underground copper mine in the north of Chile, while the stage concerning the rock pile identification was later validated using real data. The tests showed that the excavation algorithm is able to load the material with an average of 90% bucket fill factor using between three and four attempts (professional human operators required between two and three loading attempts in this mine).es_ES
Patrocinadordc.description.sponsorshipChilean National Research Agency ANID AFB180004 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 1201170es_ES
Lenguagedc.language.isoenes_ES
Publisherdc.publisherMDPIes_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
Sourcedc.sourceApplied Sciences-Baseles_ES
Keywordsdc.subjectAutonomous loading systemes_ES
Keywordsdc.subjectField roboticses_ES
Keywordsdc.subjectMining automationes_ES
Títulodc.titleAutonomous loading system for load-haul-dump (LHD) machines used in underground mininges_ES
Document typedc.typeArtículo de revistaes_ES
dc.description.versiondc.description.versionVersión publicada - versión final del editores_ES
dcterms.accessRightsdcterms.accessRightsAcceso abiertoes_ES
Catalogueruchile.catalogadorcfres_ES
Indexationuchile.indexArtículo de publícación WoSes_ES
Indexationuchile.indexArtículo de publicación SCOPUSes_ES


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States