An Interface Platform for Robotic Neuromorphic Systems

Author:

Russo Nicola1ORCID,Huang Haochun2,Donati Eugenio1ORCID,Madsen Thomas1ORCID,Nikolic Konstantin12ORCID

Affiliation:

1. School of Computing and Engineering, University of West London, London W5 5RF, UK

2. Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, UK

Abstract

Neuromorphic computing is promising to become a future standard in low-power AI applications. The integration between new neuromorphic hardware and traditional microcontrollers is an open challenge. In this paper, we present an interface board and a communication protocol that allows communication between different devices, using a microcontroller unit (Arduino Due) in the middle. Our compact printed circuit board (PCB) links different devices as a whole system and provides a power supply for the entire system using batteries as the power supply. Concretely, we have connected a Dynamic Vision Sensor (DVS128), SpiNNaker board and a servo motor, creating a platform for a neuromorphic robotic system controlled by a Spiking Neural Network, which is demonstrated on the task of intercepting incoming objects. The data rate of the implemented interface board is 24.64 k symbols/s and the latency for generating commands is about 11ms. The complete system is run only by batteries, making it very suitable for robotic applications.

Publisher

MDPI AG

Reference25 articles.

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3. Wei, D., and Harris, J.G. (2004, January 23–26). Signal reconstruction from spiking neuron models. Proceedings of the 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), Vancouver, BC, Canada.

4. The SpiNNaker project;Furber;Proc. IEEE,2014

5. Interfacing real-time spiking i/o with the spinnaker neuromimetic architecture;Davies;Aust. J. Intell. Inf. Process. Syst.,2010

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