Spiking neural building block robot with Hebbian learning

We developed spiking neural network control for a modular robotic system. The modular robotic system can be easily assembled by a user who is allowed to make overall behaviors by assembling the physical structure made up of a number of modules. The control of each module (building block) is implemented as a spiking neuron and action potentials are sent through the communication channels of the building blocks. We show how to make a mobile robot with these spiking neural building blocks. Hebbian learning is then applied to the spiking neuron building blocks in order to allow the mobile robot to adapt to changing environmental conditions. Collected data shows the learning process, sensor adaptation and performance on a simple task for the mobile robot made out of spiking neural building blocks.