When I first built the touch classifier, I trained the kNN on data recorded from the very first device. It worked well on that one unit.

Then I started building the others, in different housings, and the model fell apart. It took me a while to see why. The touch area is copper tape, and on every build the tape ends up sitting a little differently. Slightly different placement, slightly different contact, and the capacitance signal shifts just enough that the data from the first device doesn't hold for the next one.

I can't sit with every unit, hook it to a laptop, and recollect and retrain by hand. That doesn't scale, and it isn't how I wanted this to work anyway.

So the last thing I built for this version is on-device touch tuning. You record a few of your own sample touches right on the device, and the kNN improves from them. No laptop, no reflashing. Each MiniSoul calibrates to its own hardware, and to the hand that holds it.

It felt like the right note to finish on. The behaviour engine already lets each unit drift into its own personality over time. Now even the sensing starts fresh on every one and learns its owner from the first touch.

I also built it in all the colours now. Seeing the green, yellow and pink ones lined up together and finished, it finally looks like the thing I had in my head four months ago.

And that's where this version ends. The first MiniSoul goes to my sister, the way I planned from the start. This whole project began with a cat in my hostel that decided, for no reason I could name, to form a connection with me.

Check more here: https://minisoul.thesoulbot.com

Here's the 4 months put into 40 seconds