README.md

metadata

title: Microduck Sandbox
emoji: 🐤
colorFrom: yellow
colorTo: gray
sdk: static
pinned: false

Microduck RL playground

Real trained RL policies for the Microduck robot, running fully in the browser: MuJoCo compiled to WebAssembly steps the physics, onnxruntime-web runs the policy network at 50 Hz. No server, no backend.

Policies

Button	Checkpoint	What it does
Run	BEST_alpha_walking.onnx	Velocity-tracking locomotion (arrows / WASD to steer)
Sit	BEST_alpha_sitstand.onnx	Sits down on its hull, stands back up
Roll	roulade.onnx	Rolls over and recovers

Policies and MJCF model from apirrone/microduck_runtime and apirrone/mjlab_microduck.

Controls

• Arrow up / down: forward / back
• Arrow left / right: turn
• A / E: strafe
• Space: roll (one barrel roll, then back to running)
• R: reset
• Drag to orbit, scroll to zoom
• Colour dots: repaint the duck (it quacks)

Gamepad

Plug in a controller and the same mapping as the real robot runtime applies:

• Left stick: forward / back + strafe
• Right stick: turn
• X: roll
• D-pad down: sit / stand toggle
• Right trigger: mouth (analog) + quack

How it works

• rl.js fetches the MJCF (robot_allcollisions.xml), strips the visual geoms, injects a floor and a STAND keyframe, and compiles it with the official @mujoco/mujoco WASM bindings.
• The 61D observation (gyro, projected gravity, joint pos/vel, last action, command) matches mjlab_microduck/scripts/infer_policy.py.
• Rendering is a three.js rig built from kinematics.json + decimated STL meshes, driven directly from MuJoCo qpos.