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Sensor architecture and task classification for agricultural vehicles and environments

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Sensor architecture and task classification for agricultural vehicles and environments

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dc.contributor.author Rovira Más, Francisco es_ES
dc.date.accessioned 2017-01-09T13:23:59Z
dc.date.available 2017-01-09T13:23:59Z
dc.date.issued 2010-12
dc.identifier.issn 1424-8220
dc.identifier.uri http://hdl.handle.net/10251/76473
dc.description.abstract [EN] The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way es_ES
dc.description.sponsorship The research activities devoted to the study of sensor and system architectures for agricultural intelligent vehicles carried out during 2010 have been supported by the Spanish Ministry of Science and Innovation through Project AGL2009-11731. en_EN
dc.language Inglés es_ES
dc.publisher MDPI es_ES
dc.relation info:eu-repo/grantAgreement/MICINN//AGL2009-11731/ES/Percepcion Tridimensional Para Robotica Agricola/ es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Sensor architecture es_ES
dc.subject Intelligent vehicles es_ES
dc.subject Off-road autonomous vehicles es_ES
dc.subject Robotics es_ES
dc.subject Precision agriculture es_ES
dc.subject.classification INGENIERIA AGROFORESTAL es_ES
dc.title Sensor architecture and task classification for agricultural vehicles and environments es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s101211226
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural es_ES
dc.description.bibliographicCitation Rovira Más, F. (2010). Sensor architecture and task classification for agricultural vehicles and environments. Sensors. 10(12):11226-11247. https://doi.org/10.3390/s101211226 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://dx.doi.org/10.3390/s101211226 es_ES
dc.description.upvformatpinicio 11226 es_ES
dc.description.upvformatpfin 11247 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 10 es_ES
dc.description.issue 12 es_ES
dc.relation.senia 39076 es_ES
dc.identifier.pmid 22163522 en_EN
dc.identifier.pmcid PMC3231084 en_EN
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES


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