Code

About this Page

If you want to get straight to it, here’s my repo https://github.com/Apollonius14 and I try to learn the basics of things like this:

ezgif.com-crop
Agonising but ultimately worthwhile computer vision and particle filter MOOC on Coursera

Design and hardware are great, but unless you intend to carry your products around it helps to instruct them to do something automatically. Since the theme of this website is mobility, I will be reviewing learning resources that help us control robots to sense the world, decide what to do, and control their bodies to carry out the required actions.

My mission is to demystify, within my ability, buzzwords like machine learning and robotics. A lot of it will follow my own journey to build my own smart mobility systems.

Disclaimer: I’m average (at best) at coding in that I taught myself and only programme sporadically in my private time. Please don’t expect best practices here, but if you’re curious about how machines learn, make decisions and move I think you may find this enjoyable, and maybe useful!

  1. How do robots know where they are?
  2. How do robots see?

GitHub Repo

https://github.com/Apollonius14

Pseudocode Example

I’ve personally learned more from a few pages of clearly thought out pseudocode than a few semesters of C++ “basics” at uni. I’ll try my best to explain my code like this:

# Taking a step back from syntax

Do this 5 times, or until you lose patience:

   {
   Read this line;
   If it makes sense: say these numbers;
   If it doesn't: say these numbers;
   };

Create a matrix of dimensions 4x4
Fill it with random integers between -5 and 3
Invert it and multiply it with [x y z theta] transposed

      "hang on, what are x, y, z and theta?"

Clarify of thought, structure, and a steady eye on the end goal will get you far. There are elegant ways to do things, there are efficient ways to use resources and there are clever mathematical shortcuts to operations. There are crude but powerful approximations.

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