We describe a model and implementation of evolutionary spiking
neurons
for embedded microcontrollers with few
bytes of memory and very low power consumption. The approach is
tested with an autonomous microrobot
of less than 1
in
3 that evolves the ability to move in a small maze without
human intervention and external computers. Considering the very
large diffusion, small size, and low cost of embedded
microcontrollers, the approach described here could find its way in
several intelligent devices with sensors and/or actuators, as well
as in smart credit cards.