A SpiNNaker Application: Design, Implementation and Validation of SCPGs

Cuevas Arteaga, Brayan; Domínguez Morales, Juan Pedro; Rostro González, Horacio; Espinal, Andrés; Jiménez Fernández, Ángel Francisco; Gómez Rodríguez, Francisco de Asís; Linares Barranco, Alejandro

doi:10.1007/978-3-319-59153-7_47

Ponencia

dc.creator	Cuevas Arteaga, Brayan	es
dc.creator	Domínguez Morales, Juan Pedro	es
dc.creator	Rostro González, Horacio	es
dc.creator	Espinal, Andrés	es
dc.creator	Jiménez Fernández, Ángel Francisco	es
dc.creator	Gómez Rodríguez, Francisco de Asís	es
dc.creator	Linares Barranco, Alejandro	es
dc.date.accessioned	2020-01-22T08:49:52Z
dc.date.available	2020-01-22T08:49:52Z
dc.date.issued	2017
dc.identifier.citation	Cuevas Arteaga, B., Domínguez Morales, J.P., Rostro González, H., Espinal, A., Jiménez Fernández, Á.F., Gómez Rodríguez, F.d.A. y Linares Barranco, A. (2017). A SpiNNaker Application: Design, Implementation and Validation of SCPGs. En IWANN 2017: 14th International Work-Conference on Artificial Neural Networks (548-559), Cadiz, España: Springer.
dc.identifier.isbn	978-3-319-59152-0	es
dc.identifier.issn	0302-9743	es
dc.identifier.uri	https://hdl.handle.net/11441/92068
dc.description.abstract	In this paper, we present the numerical results of the implementation of a Spiking Central Pattern Generator (SCPG) on a SpiNNaker board. The SCPG is a network of current-based leaky integrateand- fire (LIF) neurons, which generates periodic spike trains that correspond to different locomotion gaits (i.e. walk, trot, run). To generate such patterns, the SCPG has been configured with different topologies, and its parameters have been experimentally estimated. To validate our designs, we have implemented them on the SpiNNaker board using PyNN and we have embedded it on a hexapod robot. The system includes a Dynamic Vision Sensor system able to command a pattern to the robot depending on the frequency of the events fired. The more activity the DVS produces, the faster that the pattern that is commanded will be.	es
dc.description.sponsorship	Ministerio de Economía y Competitividad TEC2016-77785-P	es
dc.format	application/pdf	es
dc.language.iso	eng	es
dc.publisher	Springer	es
dc.relation.ispartof	IWANN 2017: 14th International Work-Conference on Artificial Neural Networks (2017), p 548-559
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	SCPGs	es
dc.subject	Legged robots locomotion	es
dc.subject	SpiNNaker	es
dc.subject	Spiking neurons	es
dc.subject	Hardware based implementations	es
dc.title	A SpiNNaker Application: Design, Implementation and Validation of SCPGs	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dcterms.identifier	https://ror.org/03yxnpp24
dc.type.version	info:eu-repo/semantics/submittedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores	es
dc.relation.projectID	TEC2016-77785-P	es
dc.relation.publisherversion	https://link.springer.com/chapter/10.1007/978-3-319-59153-7_47	es
dc.identifier.doi	10.1007/978-3-319-59153-7_47	es
dc.contributor.group	Universidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación	es
idus.format.extent	12	es
dc.publication.initialPage	548	es
dc.publication.endPage	559	es
dc.eventtitle	IWANN 2017: 14th International Work-Conference on Artificial Neural Networks	es
dc.eventinstitution	Cadiz, España	es
dc.relation.publicationplace	Berlin	es

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