Real-time interface board for closed-loop robotic tasks on the SpiNNaker neural computing system

Various custom hardware solutions for simulation of neural circuitry have recently been developed, each focusing on particular aspects such as low power operation, high computation speed, or biologically detailed simulations. The SpiNNaker computing system has been developed to simulate large spiking neural circuits in real-time in a network of parallel operating microcontrollers, interconnected by a high-speed asynchronous interface. A potential application area is autonomous mobile robotics, which would tremendously benefit from on-board simulations of networks of tens of thousands of spiking neurons in real-time. Currently, the SpiNNaker hardware circuit boards provide a single Ethernet interface for booting, debug, and input and output of data, which results in a severe bottleneck for sensory perception and motor control signals. This paper describes a small and flexible real-time I/O-hardware interface to connect external devices such as robotic sensors and actuators directly to the fast asynchronous internal communication infrastructure of the SpiNNaker neural computing system. We evaluate performance in terms of package throughput and present a simple application demonstration of a closed loop mobile robot interpreting visual data to approach the most salient stimulus. © 2013 Springer-Verlag Berlin Heidelberg.