Publication:
Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications

dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Robótica (Robotics Lab)es
dc.contributor.authorFernández Fernández, Raúl
dc.contributor.authorGonzález Víctores, Juan Carlos
dc.contributor.authorEstévez Fernández, David
dc.contributor.authorBalaguer Bernaldo de Quirós, Carlos
dc.date.accessioned2019-02-05T11:22:25Z
dc.date.available2019-02-05T11:22:25Z
dc.date.issued2018-11-07
dc.description.abstractOne of the most important challenges of Smart City Applications is to adapt the system to interact with non-expert users. Robot imitation frameworks aim to simplify and reduce times of robot programming by allowing users to program directly through action demonstrations. In classical robot imitation frameworks, actions are modelled using joint or Cartesian space trajectories. They accurately describe actions where geometrical characteristics are relevant, such as fixed trajectories from one pose to another. Other features, such as visual ones, are not always well represented with these pure geometrical approaches. Continuous Goal-Directed Actions (CGDA) is an alternative to these conventional methods, as it encodes actions as changes of any selected feature that can be extracted from the environment. As a consequence of this, the robot joint trajectories for execution must be fully computed to comply with this feature-agnostic encoding. This is achieved using Evolutionary Algorithms (EA), which usually requires too many evaluations to perform this evolution step in the actual robot. The current strategies involve performing evaluations in a simulated environment, transferring only the final joint trajectory to the actual robot. Smart City applications involve working in highly dynamic and complex environments, where having a precise model is not always achievable. Our goal is to study the tractability of performing these evaluations directly in a real-world scenario. Two different approaches to reduce the number of evaluations using EA, are proposed and compared. In the first approach, Particle Swarm Optimization (PSO)-based methods have been studied and compared within the CGDA framework: naïve PSO, Fitness Inheritance PSO (FI-PSO), and Adaptive Fuzzy Fitness Granulation with PSO (AFFG-PSO).en
dc.description.sponsorshipThe research leading to these results has received funding from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos. fase III; S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU.en
dc.format.extent19
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationFernández-Fernández, R., Victores, J.G., Estévez, D., Balaguer, C. (2018). Real Evaluations Tractability using Continuous Goal- Directed Actions in Smart City Applications. Sensors, 18 (11), 3818.en
dc.identifier.doihttps://doi.org/10.3390/s18113818
dc.identifier.issn1424-8220
dc.identifier.publicationissue11
dc.identifier.publicationtitleSensorsen
dc.identifier.publicationvolume18
dc.identifier.urihttps://hdl.handle.net/10016/27992
dc.identifier.uxxiAR/0000022412
dc.language.isoengen
dc.publisherMDPIen
dc.relation.projectIDComunidad de Madrid. S2013/MIT-2748es
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaRobótica e Informática Industriales
dc.subject.otherSmart Cityen
dc.subject.otherCGDAen
dc.subject.otherEvolutionary algorithmsen
dc.subject.otherPbDen
dc.subject.otherLfDen
dc.subject.otherEvaluationsen
dc.subject.otherHumanoids robotsen
dc.subject.otherConstraintsen
dc.subject.otherPSOen
dc.subject.otherFitness inheritanceen
dc.subject.otherReal worlden
dc.titleReal Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applicationsen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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