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Showing posts from February, 2021

Most viewed post - Feb 2021 on Robots and Physical computing Blog

Click on the links in red to read more. Explaining the Tinkercad microbit Neural network In a previous post, I looked at developing a neural network in Tinkercad around the Microbit (details available here ) and the whole model ... Making a neural network in Tinkercad from Microbits Tinkercad and microbit neural network In a previous post I produced a single neuron based around microbits in Tickercad - see here . To exte... VR robot in a maze - from Blocks to Python Recently I produced a post about playing with Vex Robotics VexCode VR blocks and the Maze Playground. The post finished with me saying I w... Easy, Free and no markers Augmented Reality - location based AR For a few years, I have been a fan of Aframe and AR.js - these are fantastic tools for creating web-based Virtual and Augmented Reality.  No... Tinkercad and Microbit: To make a neuron The free online CAD (and so much more) package Tinkercad  https://www.tinkercad.com/ under circuits; now has microbits as part of...

Build yourself a Planet - Web VR

Using Mozzila's brilliant AFrame, a web-based Virtual Reality model of a planet with rings and include a moon with an image on it. Step 1. Basic Planet The first step is to set a new site in  Glitch.com  and then add a white sphere on a black background. <html>   <head>     <script src="https://aframe.io/releases/1.5.0/aframe.min.js"></script>   </head>   <body>     <a-scene>      <a-sphere position="0 1.25 -5" radius="3" color="white" >       </a-sphere>          <a-sky color="black"></a-sky>     </a-scene>   </body> </html>     Using the Aframe 'tags' to create a white sphere and to create a black background Step 2: Rotate the planet and add some colour Now we can add a surface to the ...

VR robot in a maze - from Blocks to Python

Recently I produced a post about playing with Vex Robotics VexCode VR blocks and the Maze Playground. The post finished with me saying I would like to play with Python and do a Python version of it. Well it is actually very easy to do it. You can do it in two stages from the block code. First click on the <> icon (lighted in the figure above and it gives a further view producing Python code that changes as you change the blocks. The last stage is to convert to a text project (button at the bottom right of the screen. Example of the code. myVariable = 0 def when_started1(): global myVariable drivetrain . drive_for ( FORWARD , 100 , MM ) while not down_eye . detect ( RED ): drivetrain . drive_for ( FORWARD , 5 , MM ) if right_bumper . pressed (): drivetrain . drive_for ( REVERSE , 30 , MM ) drivetrain . turn_for ( LEFT , 20 , DEGREES ) drivetrain . drive_for ( FORWARD , 20 , MM ) else : if l...

Escape the Maze with a VR robot - Vex VR

You don't need to buy a robot to get programming a robot, now there are a range of free and relatively simple to start with robot simulators to play with. Three examples are listed below: - Make code for Lego EV3  https://robotsandphysicalcomputing.blogspot.com/2020/05/programming-robots-virtually-3-lego-ev3.html   - i Robot simulator  https://robotsandphysicalcomputing.blogspot.com/2020/04/programming-robots-virtually-2-irobot.html - Vex robotics Vexcode VR   https://robotsandphysicalcomputing.blogspot.com/2020/04/programming-robots-virtually-1-vexcode.html   It is the last one of these ( https://www.vexrobotics.com/vexcode-vr ) that is the focus of this post and return to hit, after an earlier discussion in  https://robotsandphysicalcomputing.blogspot.com/2020/04/programming-robots-virtually-1-vexcode.html   .  Two of the nice things about the package, apart from being free, are it uses a Scratch-like programming language and it provides a ...

Explaining the Tinkercad microbit Neural network

In a previous post, I looked at developing a neural network in Tinkercad around the Microbit (details available here ) and the whole model can be found at    https://www.tinkercad.com/things/hPV4nU0Asr5-smooth-bojo   Quick overview of a simple neural network; at its simplest, it has at least three layers of neurons where the output of the first layer's neuron, the input layer, is connected as an input to every neuron in the next layer, the hidden layer. The output of the neurons in the hidden layer connects as inputs to every neuron in the final output layer - which gives the outputs from the network. The figure below gives an overview; neurons are processing units. Well, sort of. Neurons as processing units is certainly true for the hidden and the output layers. It is not true, though, for the input layer; this is literally a layer of inputs with no processing going on.  So going back to the first figure of tinkercad microbit neural network and comparing it with th...

Making a neural network in Tinkercad from Microbits

Tinkercad and microbit neural network In a previous post I produced a single neuron based around microbits in Tickercad - see here . To extend this the basic ideas discussed in that the previous post where extended to three microbit joined together. In  other words a network of neurones or neural network. Basic requirements of a neuron are Requirements  - By altering the bias (or w0 in the example), weights change the behaviour of switches changes. -when switch is pressed a variable x1 or x2 is set to 1 depending on which button is pressed and when released it goes to 0.  - if (bias+w1*x1+w2*x2)>=0 then a T for True appears of the LEDs otherwise F for False is shown. So by selecting the weights and connecting the outputs (p2) from the microbits labelled as Red and Green in the image above as inputs to the yellow microbit 'neuron' we can form a neural network. Switches as the inputs and the screen on the yellow 'neuron' as the output of the network showing true (T) or...