Humanoid — Unitree H1

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The prompt

set up a Unitree H1 from mujoco_menagerie standing on flat ground,
write a PD controller that holds the default standing keyframe on
all 19 joints with stiff hips and ankles, run 5 seconds headless,
and log IMU accel + gyro, base position + orientation, and all 19
joint angles + torques to sensor_log.csv

• Asks where mujoco_menagerie lives, or clones it to a path you confirm
• Composes h1_scene.xml that <include>s the Menagerie H1 and adds a 10×10m floor
• Spawns the H1 at the default keyframe’s qpos so the feet rest cleanly on the ground
• Writes a run_sim.py that:
  • Loads the H1 keyframe pose as the joint-target reference
  • Applies a per-joint PD controller — an initial gain set with stiffer hips and ankles, lighter arms (the common starting point for hold-pose stability; expect to retune)
  • Steps at 1 ms timestep with implicitfast integrator
  • Logs sensors at 200 Hz
• Runs headless, prints the final base height and orientation drift, and notes any contact issues

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What ends up on disk

your-project/
├── h1_scene.xml            # floor + Menagerie H1 include
├── run_sim.py              # full-body PD hold-pose + sensor logger
├── sensor_log.csv          # 1000 rows: IMU, base pose, 19 joints (pos + torque)
└── DRIFT.md                # scene summary, gains used, what to iterate

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What the viewer shows

open h1_scene.xml in the MuJoCo viewer

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Iterating from here

add a small perturbation: apply a 30N forward push to the H1's
torso at t=2s for 50ms, see if it recovers
add stairs in front of the H1 and have it step forward onto the
first step (lift right foot, plant, shift weight)
load an MPC walking controller from /path/to/h1_mpc and bridge it
to the joint targets — log the contact schedule and CoM trajectory
add a head-mounted RGB camera and stream 30fps frames
write a ROS2 bridge: publish /h1/joint_states, /h1/imu, /h1/base_pose
and subscribe to /h1/joint_cmd for external controllers
load /path/to/h1_walking_policy.onnx and step it every 20ms,
feeding the standard humanoid observation (joint pos + vel + IMU +
base height), outputting target joint positions

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Honest scope

• Compose the scene around the Menagerie H1 model
• Write a full-body PD hold-pose controller (stiff hips/ankles, lighter arms)
• Wire IMU + base pose + 19-joint sensors and log them
• Open the viewer / run headless

• Bipedal walking — even “in place” walking is non-trivial; you need a controller (MPC, learned policy, or a reference trajectory tracker), not Drift
• Push recovery beyond what hold-pose PD naturally absorbs
• Whole-body control with operational-space inverse dynamics — Drift can scaffold the controller skeleton but the math is yours
• Sim-to-real — H1 sim parameters are good but not identical to hardware

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Common gotchas

spawn the H1 facing -Y instead of +X

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Next steps