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g1-amp-motion
BlackCatRoboticsAI/g1-amp-motion
g1-amp-motion is a machine learning model from BlackCatRoboticsAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Unitree G1 Humanoid Motion Imitation (AMP) — 494 human motion capture sequences from the AMASS dataset, trained using Adversarial Motion Priors (AMP) in Isaac Lab.
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Updated Sep 3, 2026
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.pt29.1 MB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- Sep 3, 2026
- Updated
- Sep 3, 2026
- SHA
- 73aa7b2f
Model card
From the Hugging Face model README
G1-AMP Motion Imitation Policy
Unitree G1 Humanoid Motion Imitation (AMP) — 494 human motion capture sequences from the AMASS dataset, trained using Adversarial Motion Priors (AMP) in Isaac Lab.
Model Details
| Field | Value |
|---|---|
| License | MIT (commercial use ✅) |
| Robot | Unitree G1 (37 DOFs, 23 active) |
| Input | 216-dim observations (joint pos/vel, root state, future reference targets) |
| Output | 23-dim joint position targets (scale by 0.5) |
| Framework | Isaac Lab / PyTorch |
| Format | TorchScript (policy_jit.pt = 2.9MB) |
Performance
| Metric | Value |
|---|---|
| Total Reward (mean) | 160.29 |
| Episode Length (mean) | 396.9 / 400 steps |
| Tracking Reward (mean) | 0.317 |
Quick Start
import torch
import numpy as np
# Load policy
model = torch.jit.load("policy_jit.pt")
model.eval()
# Run inference
obs = torch.randn(1, 216) # Replace with actual observations
with torch.no_grad():
actions = model(obs) # (1, 23) joint position targets
actions = actions * 0.5 # Scale before sending to robot
Files
policy_jit.pt— JIT-traced policy for deployment (2.9MB)best_agent.pt— Full checkpoint for resuming training (25MB)
Training Details
- Motion Dataset: 494 AMASS motions (~113 min, 196,642 frames)
- Algorithm: AMP (Adversarial Motion Priors) via skrl
- Training Hardware: NVIDIA RTX 4080 SUPER (16GB VRAM)
- Training Duration: 5.5 days (12.4M timesteps)
- Domain Randomization: Mass, friction, PD gains, action delay
Citation
@misc{pathonai2026g1imitate,
title={G1 Humanoid Motion Imitation with AMP in Isaac Lab},
author={PathOn-AI},
year={2026},
publisher={Hugging Face},
url={https://huggingface.co/PathOn-AI/g1-imitate-isaaclab-amp}
}
License
MIT License — free for commercial and non-commercial use.
- License
- mit
- Created
- Sep 3, 2026
- Updated
- Sep 3, 2026