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Showing posts from April, 2018

Summary of Robots at BCS Northampton

On the 17th April 2018 I had the honour of presenting a public talk on robots for the Northampton Branch of the Britsh Computer Society (BCS). This post aims to summarise the session. The session was really from a personal perspective and journey, covering where I think robots in home and schools are going, and an overview of some of the projects I have been involved. First, part was the presentation - the slides are shown below. Robots Talk British Computer Society Northampton_17_4_2018 from Scott Turner The videos used in the presentations are shown below. The first video is an introduction and welcome from Red the Nao robot. Next video shows a programmed Cozmo, using Anki's graphical programming language. Second section of the session was playing with the robots. Red the Nao , an Anki Cozmo and an UBtech Alpha2 and having a play with a Crumble -based junkbots.  Crumble junkbots were used on PC and Raspberry Pi via Pi-top CEED . Red ...

How to produce a Microbit neural network

This is really part two of a set of post  in response to a question from Carl Simmons ( @Activ8Thinking ) concerning building a   micro:bit  simple neuron.  In the previous post a single neuron was produced. This post looks at producing a network of neurons, ie. neural network; looking to solve the problem that a single neuron can't solve, making an Exclusive OR gate (XOR) 1. Quick Overview 1.1 The neuron itself Inputs are going to be binary Weighted sum is bias+W1*input1+w2*input2 If weighted sum>=0 then the output is True (T on the LEDs) or '1' If weighted sum<0 then the output is False (F on the LEDs) or '0' 1.2 The XOR Essentially for the two input case if the two inputs are different then the output is True. The figure below shows the arrangement of the connections; pin 2 is the output of the neurons. The two micro:bits/neurons on the left of the picture taking in the two inputs, the same inputs go to these two neurons; the ...