TY - GEN
T1 - A SpiNNaker application
T2 - 14th International Work-Conference on Artificial Neural Networks, IWANN 2017
AU - Cuevas-Arteaga, Brayan
AU - Dominguez-Morales, Juan Pedro
AU - Rostro-Gonzalez, Horacio
AU - Espinal, Andres
AU - Jimenez-Fernandez, Angel F.
AU - Gomez-Rodriguez, Francisco
AU - Linares-Barranco, Alejandro
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Hardware based implementations
KW - Legged robots locomotion
KW - SCPGs
KW - Spiking neurons
KW - SpiNNaker
UR - http://www.scopus.com/inward/record.url?scp=85020540941&partnerID=8YFLogxK
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_univeritat_ramon_llull&SrcAuth=WosAPI&KeyUT=WOS:000443108200047&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1007/978-3-319-59153-7_47
DO - 10.1007/978-3-319-59153-7_47
M3 - Conference contribution
AN - SCOPUS:85020540941
SN - 9783319591520
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 548
EP - 559
BT - Advances in Computational Intelligence - 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Proceedings
A2 - Catala, Andreu
A2 - Rojas, Ignacio
A2 - Joya, Gonzalo
PB - Springer Verlag
Y2 - 14 June 2017 through 16 June 2017
ER -