Neuromorphic robotic platform with visual input, processor and actuator, based on spiking neural networks
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Published version
Author(s)
Cheng, Ran
Mirza, Khalid B
Nikolic, Konstantin
Type
Journal Article
Abstract
This paper describes the design and modus of operation of a neuromorphic robotic platform based on SpiNNaker, and its implementation on the goalkeeper task. The robotic system utilises an address event representation (AER) type of camera (dynamic vision sensor (DVS)) to capture features of a moving ball, and a servo motor to position the goalkeeper to intercept the incoming ball. At the backbone of the system is a microcontroller (Arduino Due) which facilitates communication and control between different robot parts. A spiking neuronal network (SNN), which is running on SpiNNaker, predicts the location of arrival of the moving ball and decides where to place the goalkeeper. In our setup, the maximum data transmission speed of the closed-loop system is approximately 3000 packets per second for both uplink and downlink, and the robot can intercept balls whose speed is up to 1 m/s starting from the distance of about 0.8 m. The interception accuracy is up to 85%, the response latency is 6.5 ms and the maximum power consumption is 7.15 W. This is better than previous implementations based on PC. Here, a simplified version of an SNN has been developed for the ‘interception of a moving object’ task, for the purpose of demonstrating the platform, however a generalised SNN for this problem is a nontrivial problem. A demo video of the robot goalie is available on YouTube.
Date Issued
2020-06-24
Date Acceptance
2020-06-22
Citation
Applied System Innovation, 2020, 3 (2), pp.1-16
ISSN
2571-5577
Publisher
MDPI
Start Page
1
End Page
16
Journal / Book Title
Applied System Innovation
Volume
3
Issue
2
Copyright Statement
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.mdpi.com/2571-5577/3/2/28
Grant Number
EP/N002474/1
Publication Status
Published online
Date Publish Online
2020-06-24