zita-ch/supermimic_vibed
vibe coded supermimic within 1h, LAFAN passed within 1.5 gpuh training
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README & documentation
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Unofficial reproduction of SuperMimic: Scaling Humanoid Whole-Body Control with One Differentiable World Model (arXiv 2610.28480) — no official code is released, so everything here is implemented from the paper. Target experiment: the controlled LAFAN1 comparison (Fig. 4a): 40 G1-retargeted LAFAN1 clips (2.45 h), one GPU; the paper reaches evaluation normalized return 0.82 after 1.2 h on an H100. Author: Chong Zhang (ETH Zurich). License: MIT. Solid robot: the trained policy simulated in Isaac Lab with MuJoCo-Warp. Blue ghost: the reference motion. Clips: dance, jumps, fall-and-get-up, sprint. Progress and timestamps: MILESTONES.md. Neither Isaac Lab nor any data is included in this repository; the steps below fetch them. Requirements: Linux, an NVIDIA GPU (tested: RTX PRO 6000 Blackwell, driver 580 / CUDA 13), Docker with the NVIDIA Container Toolkit (docker run --gpus must work), 20 GB of disk for the images and 0.2 GB for the data. Physics: Newton with the MuJoCo-Warp…
Read the full README ↗ · Preview checked 2026-10-28T22:22:40.996Z
Inside the original README — Document outline
- SuperMimic reproduction on Isaac Lab 3 (kit-less, MuJoCo-Warp)
- Layout
- Setup
- 1. Isaac Lab (kit-less Docker image)
- 2. Data: LAFAN1 motions and the G1 model
- Usage
- Result (LAFAN1, 40 clips, one RTX PRO 6000 Blackwell)
- Implementation (paper section -> file)
- Deviations / choices not specified by the paper
- Attribution and licenses
- License
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What this repository does
vibe coded supermimic within 1h, LAFAN passed within 1.5 gpuh training
Repository facts
- Owner
- zita-ch
- Primary language
- Python
- Stars
- 684
- Forks
- 68
- Open issues + pull requests
- 1
- License
- MIT
- Archived
- No
- Default branch
- main
- Created
- 2026-10-21T17:29:28.000Z
- Last push
- 2026-10-26T12:56:15.000Z
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