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An Interface Platform for Robotic Neuromorphic Systems.

Authors :
Russo, Nicola
Huang, Haochun
Donati, Eugenio
Madsen, Thomas
Nikolic, Konstantin
Source :
Chips; Mar2023, Vol. 2 Issue 1, p20-30, 11p
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26740729
Volume :
2
Issue :
1
Database :
Complementary Index
Journal :
Chips
Publication Type :
Academic Journal
Accession number :
162747536
Full Text :
https://doi.org/10.3390/chips2010002