Build a Reachy Mini MuJoCo simulation on Raspberry Pi
Introduction
Learn about Reachy and the Reachy Gladiator application
Start the Reachy simulation on MuJoCo
Set up the Raspberry Pi and run the edge AI app
Use the Reachy Gladiator application
Understand the Reachy Gladiator application code
(Optional) Extend the project
Next Steps
Build a Reachy Mini MuJoCo simulation on Raspberry Pi
Review frequently asked questions
These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
If you use VS Code Remote SSH port forwarding, open
http://localhost:8042 on your laptop. Otherwise, browse to http://<pi-ip-address>:8042 from any machine on the same network.Run
hostname -I on the Raspberry Pi to print its IP address. Then use that address with port 8042 in your browser.Check that
assets/gesture_recognizer.task exists as a real model file, not a tiny pointer file. If you cloned before enabling Git LFS, enable LFS and re-clone the repository.Verify the MuJoCo simulation is running on your development machine and that the Pi can reach it over the network. Also review
main.py because it contains the settings used for the distributed simulation route.You should see the simulated Reachy Mini play a victory or defeat motion, and the web dashboard should reflect the verdict. This indicates the camera, inference, network, and simulator are connected end to end.