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Conference object . 2016
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https://doi.org/10.5281/zenodo...
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Low-Cost Visually Intelligent Robots With Eot

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type , Article 01 Jan 2016Publisher:ZenodoJournal:Robotics: Science and Systems, Workshop Are the Sceptics Right? Limits and Potentials of Deep Learning in Robotics (RSS)Funded by:EC | EoT
Authors: Moloney, David; Pena, Dexmont; Dunne, Aubrey; Dehghani, Alireza; Baugh, Gary; Caulfield, Sam; Lee, Kevin; +7 Authors

doi: 10.5281/zenodo.56226

Low-Cost Visually Intelligent Robots With Eot

Abstract

This paper describes the development of a low-cost, low-power visual-intelligence and robotics platform based on the H2020 EoT (Eyes of Things platform) and the Movidius Myriad2 VPU (Vision Processing Unit), associated machine vision, communications and motor-control libraries and the Movidius Fathom deep-learning framework. The platform allows a variety of low-cost robots to be built using kits and programmed in micropython. The ultimate goal of the EoT robotics project, which is still in development, is to enable the mass-production of advanced and highly programmable robots for developers, students and hobbyists at a sub $100 price-point that includes robot, control electronics, software and an eBook.

This research was founded by EC H2020-ICT-2014-1 GA: 643924.

Keywords

vision processing unit, Computer Vision, VPU, Computational Imaging, ISA, vector processor

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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