Robots and Physical Computing

This year the Computing team has been fortunate enough to host three Nuffield Research Placement students ( https://www.nuffieldresearchplacements.org/ ) all working with Dr Scott Turner. Michael Welsh Michael has been working on using a  micro:bit based bitbot from 4tronix  to produce a potential teaching tool; an example of artificial neurons used control a robot. The aim is for this tool to be used with 3rd-year Undergraduates, as part of a module on Artificial Intelligence. Michael's solution was to use the computer to run and train a single neuron; then for the robot to send values from the line sensors back to the program running on a Computer and receive control signals.  Sounds easy? No really, in the end, the software running on the computer had to also send and receive the data through a microbit (via USB) and then use radio to communicate with the bit:bot robot. All the various developed part...

1. Single Neurone Instructions: Set the inputs by pressing the buttons marked input 1 and input 2 (Red is off(False or 0) and Green is on(True or 1)) Change the weights by changing weights 1 to 3, wx goes with input x and weight 3 is the bias. To activate the neuron you need to click on the the yellow ball ('the neuron'). The video below show it in action and explains the code. To see the code go to  https://scratch.mit.edu/projects/131892234/  . A slight modification click on the bell to change the weights The code is available at  https://scratch.mit.edu/projects/171190294/ 2. Training a Neurone In this part, the training of a neuron all written in Scratch is tackled. The video shows it action and you can have a go at using the software yourself at the end of the post. The Scratch code can be found at  https://scratch.mit.edu/projects/132915502/ All opinions in this blog are the Author's and should not in any ...

An overview of using Lego RCX  robots for teaching neural networks present at workshop in 2011. Derby presentation from Scott Turner The video below shows the robot trying out sets of weights for two neurones, until a set of weights are found that enable the robot to go around the circle. As a part of a set of tools I have found the following useful for teaching the principles of simple neurones.  Example code: import josx.platform.rcx.*; public class annlf{  public static void main(String[] args)  {   int w[][] ={//put weights here};   int o[]={1,1};   int s1,s2,res1,res2;   int sensor1=0,sensor2=0;   robot_1 tom=new robot_1();   Sensor.S1.activate();   Sensor.S3.activate();   for(;;){    sensor1=Sensor.S1.readValue();    sensor2=Sensor.S3.readValue();    LCD.showNumber(sensor1); ...