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Activie vision in robot cognition

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapt_PT
dc.contributor.advisordu Buf, J. M. H.
dc.contributor.advisorRodrigues, J. M. F.
dc.contributor.authorSaleiro, Mário Alexandre Nobre
dc.date.accessioned2017-02-14T15:03:29Z
dc.date.available2017-02-14T15:03:29Z
dc.date.issued2016-12-21
dc.date.submitted2016
dc.descriptionTese de doutoramento, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016
dc.description.abstractAs technology and our understanding of the human brain evolve, the idea of creating robots that behave and learn like humans seems to get more and more attention. However, although that knowledge and computational power are constantly growing we still have much to learn to be able to create such machines. Nonetheless, that does not mean we cannot try to validate our knowledge by creating biologically inspired models to mimic some of our brain processes and use them for robotics applications. In this thesis several biologically inspired models for vision are presented: a keypoint descriptor based on cortical cell responses that allows to create binary codes which can be used to represent speci c image regions; and a stereo vision model based on cortical cell responses and visual saliency based on color, disparity and motion. Active vision is achieved by combining these vision modules with an attractor dynamics approach for head pan control. Although biologically inspired models are usually very heavy in terms of processing power, these models were designed to be lightweight so that they can be tested for real-time robot navigation, object recognition and vision steering. The developed vision modules were tested on a child-sized robot, which uses only visual information to navigate, to detect obstacles and to recognize objects in real time. The biologically inspired visual system is integrated with a cognitive architecture, which combines vision with short- and long-term memory for simultaneous localization and mapping (SLAM). Motor control for navigation is also done using attractor dynamics.pt_PT
dc.identifier.tid101317034pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.1/8985
dc.language.isoengpt_PT
dc.relationA neuro-dynamic framework for cognitive robotics: scene representations, behavioural sequences, and learning.
dc.relationACTIVE VISION IN ROBOT COGNITION
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectKeypoint descriptorspt_PT
dc.subjectCognitive roboticspt_PT
dc.subjectStereo visionpt_PT
dc.subjectActive visionpt_PT
dc.subjectSLAMpt_PT
dc.subjectObject recognitionpt_PT
dc.titleActivie vision in robot cognitionpt_PT
dc.typedoctoral thesis
dspace.entity.typePublication
oaire.awardTitleA neuro-dynamic framework for cognitive robotics: scene representations, behavioural sequences, and learning.
oaire.awardTitleACTIVE VISION IN ROBOT COGNITION
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F50009%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/EC/FP7/270247/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F71831%2F2010/PT
oaire.fundingStream5876
oaire.fundingStreamFP7
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typedoctoralThesispt_PT
relation.isProjectOfPublication19a727e2-d775-407f-ab10-7d5f19577e08
relation.isProjectOfPublicationef5f67fa-93e7-4d9a-8157-a59c70c4e0d9
relation.isProjectOfPublication3c1f3b62-c07d-4f7a-8bb4-a791a9463e47
relation.isProjectOfPublication.latestForDiscoveryef5f67fa-93e7-4d9a-8157-a59c70c4e0d9
thesis.degree.grantorUniversidade do Algarve, Faculdade de Ciências e Tecnologia
thesis.degree.levelDoutor
thesis.degree.nameEngenharia Informáticapt_PT

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