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Adaptive robust control and admittance control for contact-driven robotic surface conditioning

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Adaptive robust control and admittance control for contact-driven robotic surface conditioning

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dc.contributor.author Solanes Galbis, Juan Ernesto es_ES
dc.contributor.author Gracia Calandin, Luis Ignacio es_ES
dc.contributor.author Muñoz-Benavent, Pau es_ES
dc.contributor.author Esparza Peidro, Alicia es_ES
dc.contributor.author Valls Miro, Jaime es_ES
dc.contributor.author Tornero Montserrat, Josep es_ES
dc.date.accessioned 2020-06-03T05:53:31Z
dc.date.available 2020-06-03T05:53:31Z
dc.date.issued 2018-12 es_ES
dc.identifier.issn 0736-5845 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145125
dc.description.abstract [EN] This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown. es_ES
dc.description.sponsorship This work was supported in part by the Spanish Government under the Project DPI2017-87656-C2-1-R and the Generalitat Valenciana under Grants VALi+d APOSTD/2016/044 and BEST/2017/029. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation GV/BEST/2017/029 es_ES
dc.relation GENERALITAT VALENCIANA/APOSTD/2016/044 es_ES
dc.relation info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2017-87656-C2-1-R/ES/VISION ARTIFICIAL Y ROBOTICA COLABORATIVA EN PULIDO DE SUPERFICIES EN LA INDUSTRIA/ es_ES
dc.relation.ispartof Robotics and Computer-Integrated Manufacturing es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Robot force control es_ES
dc.subject Adaptive switching gain es_ES
dc.subject Sliding mode control es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Adaptive robust control and admittance control for contact-driven robotic surface conditioning es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.rcim.2018.05.003 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Solanes Galbis, JE.; Gracia Calandin, LI.; Muñoz-Benavent, P.; Esparza Peidro, A.; Valls Miro, J.; Tornero Montserrat, J. (2018). Adaptive robust control and admittance control for contact-driven robotic surface conditioning. Robotics and Computer-Integrated Manufacturing. 54:115-132. https://doi.org/10.1016/j.rcim.2018.05.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.rcim.2018.05.003 es_ES
dc.description.upvformatpinicio 115 es_ES
dc.description.upvformatpfin 132 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 54 es_ES
dc.relation.pasarela S\373635 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES


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