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.Ministerio de Economía y Competitividad TEC2016-77785-
