How Kalman Filters Work
I spent quite a bit of time working through the Kalman filter content in Sebastian Thrun's book "Probabilistic Robotics"[1] a while back. I ended up making some notes [2] of the process that might be of interest to others if you're trying to get a grasp of everything that's going on with that process. One other person on the Internet that I know of thought they were useful, so I'll post the link here. This was part of a project I was working on to build a K-8 robotics curriculum (no, not teaching the kids Kalman filters, but <i>I</i> wanted to know how it all worked before starting to make a curriculum). The book is really good if you're wanting to make robots that can navigate uncertain environments.<p>Edit: I wish I'd had access to this article when I was going through that process. This is really well done.<p>1. <a href="http://amzn.com/0262201623" rel="nofollow">http://amzn.com/0262201623</a><p>2. <a href="https://github.com/aethertap/probabilistic-robotics" rel="nofollow">https://github.com/aethertap/probabilistic-robotics</a>