The Asynchronous Time-based Image Sensor (ATIS) and the Spiking Neural Network Architecture (SpiNNaker) are both neuromorphic technologies that "unconventionally" use binary spikes to represent information. The ATIS produces spikes to represent the change in light falling on the sensor, and the SpiNNaker is a massively parallel computing platform that asynchronously sends spikes between cores for processing. In this demonstration we show these two hardware used together to perform a visual tracking task. We aim to show the hardware and software architecture that integrates the ATIS and SpiNNaker together in a robot middle-ware that makes processing agnostic to the platform (CPU or SpiNNaker). We also aim to describe the algorithm, why it is suitable for the "unconventional" sensor and processing platform including the advantages as well as challenges faced.
@article{arxiv.1912.01320,
title = {ATIS + SpiNNaker: a Fully Event-based Visual Tracking Demonstration},
author = {Arren Glover and Alan B. Stokes and Steve Furber and Chiara Bartolozzi},
journal= {arXiv preprint arXiv:1912.01320},
year = {2019}
}
Comments
Presented at the Unconventional Sensing and Processing for Robotic Visual Perception workshop at the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2 pages, 2 figures