Training a real robot to play Puckworld with reinforcement learning

After I trained an agent to play “puckworld” using Q-learning, I thought “hey, maybe I should make a real robot that learns this. It can’t be that hard, right?”

Hooooooooo boy. I did not appreciate how much harder problems in the physical world can be. Examples of amateurs doing Reinforcement Learning (RL) projects are all over the place on the internet, and robotics are certainly touted as one of the main applications for RL, but in my experience, I’ve only found a few examples of someone actually using RL to train a robot. Here’s a (very abridged!) overview of my adventure getting a robot to learn to play a game called puckworld. read more

RPi camera, part 3: a few incremental fixes

Round 3! Okay, this is where I try and polish it up in a couple ways.

Here are the things I said last time I needed to make better: read more

Motion detection with the Raspberry Pi, part 2

Hi hi!

In this post, I’m really just going to concentrate on building the whole pipeline. It’s going to be rife with inefficiencies, inaccuracies, and stuff I 100% plan on fixing, but I think it’s good to get a working product, even if it’s very flawed. Someone I once worked for told me that projects in the US gov’t kind of work that way: there was high emphasis on getting a product out the door, even if it was hacky and awful (though hopefully not). I think that makes sense a lot of the time. It’s probably more motivating to see a project that does something to completion, even if it’s crappy, than a project that is partly carefully done, but still very incomplete. A crappy car is cooler than a really nice wheel. Also, it seems like iterative, smaller fixes are relatively easy. read more

Motion detection with the Raspberry Pi, part 1

Okay Declan, let’s try making this post a short and sweet update, not a rambling Homerian epic about simple stuff.

I got a Raspberry Pi (RPi) and an RPi camera because I wanted to learn about them and mess around with them. If I could do image recognition with them, that’d be a good platform to do ML, NN, and if I got enough data, maybe even DS type stuff. Luckily, there’s a ton of resources and code out there already. I drew upon heavily from www.pyimagesearch.com, which is a REALLY useful site, explained very great for beginners. Two articles that I basically copied code from and then butchered were this and this. read more