r/StackChan

I own one of the M5Stack StackChans (CoreS3 + two Feetech SCS0009 servos) and spent the last weeks turning it into a desk assistant that talks to my own server instead of a vendor cloud. Everything is open source (MIT):

GitHub: https://github.com/7H3-CH053N/StackChan-CustomFW

What it does now:

- Head that actually moves, calmly Own servo driver with a critically damped follower (speed + acceleration limits, no overshoot), plus small gestures per emotion: nod when happy, head down when sad, look up when surprised.

- Face tracking with the built-in GC0308 camera and Espressif's esp-dl face detector (~2.5 fps). It searches once if it loses you, then rests where you usually sit, so it doesn't search all night.

- Self-hosted voice server in Docker: Gemini Live for real-time voice, Home Assistant control, calendar.

- Proactive speech: Home Assistant can make it talk without a wake word, e.g. it greets me when I arrive at the office and reminds me 15 min before meetings. It stays quiet while my mic or camera is in use.

- Animated eyes with 21 emotions, picked by the server from what it is saying.

The firmware is one patch on top of xiaozhi-esp32 (pinned commit), built with ESP-IDF 6.1; CI builds it on every push.

Honest status: it runs daily on my desk, but esp-dl's face detection still crashes now and then (the robot reboots in ~10 s). That's reported upstream and Espressif is looking at it.

Looking for people to join:

- StackChan owners who want to try it and report what happens on their unit

- Starter issues are labelled "good first issue": Japanese README, testing the English build, a clock fix on the server side

- Anyone who knows esp-dl well, or wants to try a different face model (ESPDet-Pico)

I wrote up the whole story (why I first thought servo control was impossible, the four bugs before face tracking worked, why proactive speech failed three different ways). The article is in German, browser translation works fine:

https://digitalhandwerk.rocks/ki/anpassung-der-firmware-fuer-stackchan-roboter/

Happy to answer questions here in English.

I’ve been experimenting with turning an M5Stack Stack-chan into a little mobile robot. I combined it with a LEGO motor hub and wheels, recorded driving demonstrations, and trained an ACT policy.

During supervised trials, it learned to follow a line. With a separate set of demonstrations, I also tried driving between guardrails. The video shows the build, data collection, and the wrong turns along the way 😅

Build video: https://www.youtube.com/watch?v=_1pQTt8gqZM

This is also the first showcase of what I’ve built with Robium, an open-source robotics skills repo that I recently released. I used it with AI agents to help build the software and training setup.

GitHub: https://github.com/robium-ai/robium

Has anyone else experimented with learning from demonstrations on a small wheeled robot? I’d be interested to hear what worked for you.