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Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry

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dc.contributor.authorGarriz, Carlos
dc.contributor.authorDomingo Navas, María Rosario
dc.contributor.funderAgencia Estatal de Investigación. España
dc.date.accessioned2026-01-26T18:49:37Z
dc.date.available2026-01-26T18:49:37Z
dc.date.issued2022-10-05
dc.descriptionThe registered version of this article, first published in Sensors, is available online at the publisher's website: MDPI, https://doi.org/10.3390/s22197538
dc.descriptionLa versión registrada de este artículo, publicado por primera vez en Sensors, está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/s22197538
dc.description.abstractCurrently, the high demand for new products in the automotive sector requires large investments in factories. The automotive industry is characterized by high automatization, largely achieved by manipulator robots capable of multitasking. This work presents a method for the optimization of trajectories in robots with six degrees of freedom and a spherical wrist. The optimization of trajectories is based on the maximization of manipulability and the minimization of electrical energy. For this purpose, it is necessary to take into account the kinematics and dynamics of the manipulator in order to integrate an algorithm for calculation. The algorithm is based on the Kalman method. This algorithm was implemented in a simulation of the trajectories of a serial industrial robot, in which the robot has a sealer gun located on its sixth axis and the quality of the sealer application depends directly on the orientation of the gun. During the optimization of the trajectory, the application of the sealer must be guaranteed. This method was also applied to three different trajectories in the automotive sector. The obtained results for manipulability and electrical energy consumption prove the efficiency of the algorithm. Therefore, this method searches for the optimal solution within the limits of the manipulator and maintains the orientation of the final effector. This can be used for a known trajectory.en
dc.description.provenanceMade available in DSpace on 2026-01-26T18:49:37Z (GMT). No. of bitstreams: 1 Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry.pdf: 5125095 bytes, checksum: 910b5862e9ee87290299c68db5136e9d (MD5) Previous issue date: 2022-10-05en
dc.description.sponsorshipThis research was funded by the Spanish Ministry of Science, Innovation and Universities through the RTI2018-102215-B-I00 project.
dc.description.versionversión publicada
dc.identifier.citationGarriz, C., & Domingo, R. (2022). Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry. Sensors, 22(19), 7538. https://doi.org/10.3390/s22197538
dc.identifier.doihttps://doi.org/10.3390/s22197538
dc.identifier.eissn1424-8220
dc.identifier.issn.
dc.identifier.urihttps://hdl.handle.net/20.500.14468/31575
dc.journal.issue19
dc.journal.titleSensors
dc.journal.volume22
dc.language.isoen
dc.publisherMDPI
dc.relation.centerE.T.S. de Ingenieros Industriales
dc.relation.departmentIngeniería de Construcción y Fabricación
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-102215-B-I00
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.es
dc.subject3305 Tecnología de la construcción
dc.subject.keywordsmanipulator roboten
dc.subject.keywordsKalman methoden
dc.subject.keywordstrajectory optimizationen
dc.subject.keywordsmanipulabilityen
dc.subject.keywordselectrical energyen
dc.subject.keywordssimulationen
dc.titleTrajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industryen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublication6b34d535-7b88-48ed-9206-435d40b0b5b5
relation.isAuthorOfPublication.latestForDiscovery6b34d535-7b88-48ed-9206-435d40b0b5b5
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