genesis-dc-groot-adapter

DC-GR00T — Demo-Conditioned GR00T Adapter (GENESIS)

⚠️ Under Active Development This checkpoint is a research preview. The DC-GR00T manipulation pipeline is still being actively developed and validated. Results and APIs may change without notice. Use with caution in production.

Part of the GENESIS research framework: video-conditioned robot learning.

Paper: PhysicalAgent: Towards General Cognitive Robotics with Foundation World Models

Code: github.com/jeffrinsam/GENESIS → part2_manipulation/

Model Description

DC-GR00T is a Demo-Conditioned extension of GR00T N1.6. Instead of language instructions, it accepts a reference video of a manipulation task and extracts a task embedding that conditions the DiT action head.

This repository contains a LoRA fine-tuning adapter (PEFT) trained on Unitree G1 teleop demonstrations. Load it on top of the base nvidia/GR00T-N1.6-3B model.

Architecture additions over GR00T N1.6:

• Demo encoder: SigLIP ViT-B/16 (224×224) per-frame → temporal transformer → perceiver resampler → task embedding [B, 16, 768]
• Task cross-attention: Injects task embedding into DiT action head at every block
• LoRA: r=8, α=16, applied to q/k/v/o/gate/up/down_proj layers of the language model

Target robot: Unitree G1 (43-DOF action space: arms, torso, hands, legs)

Current Status

The checkpoint was trained for 4500–5000 steps on Unitree G1 teleop data. Full validation across manipulation tasks is ongoing.

Usage

Requires the dc_groot conda environment from the GENESIS repo. See part2_manipulation/README.md.

from peft import PeftModel
from gr00t.model.demo_conditioned.dc_gr00t import DCGr00t

# Load base model
base_model = DCGr00t.from_pretrained("nvidia/GR00T-N1.6-3B")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "JeffrinSam/genesis-dc-groot-adapter")
model = model.merge_and_unload()  # optional: merge for faster inference

Or via the GENESIS inference script:

conda activate dc_groot
cd GENESIS
python part2_manipulation/inference.py \
  --adapter JeffrinSam/genesis-dc-groot-adapter \
  --demo_video reference.mp4 \
  --robot unitree_g1

Adapter Details

Citation

@article{lykov2025physicalagent,
  title     = {PhysicalAgent: Towards General Cognitive Robotics with Foundation World Models},
  author    = {Lykov, Artem and Sam, Jeffrin and Nguyen, Hung Khang and others},
  journal   = {arXiv preprint arXiv:2509.13903},
  year      = {2025}
}

Please also cite the base model:

@article{nvidia2025groot,
  title   = {GR00T N1: An Open Foundation Model for Generalist Humanoid Robots},
  author  = {NVIDIA et al.},
  year    = {2025},
  url     = {https://huggingface.co/nvidia/GR00T-N1.6-3B}
}

License

Apache 2.0. The base model (nvidia/GR00T-N1.6-3B) is subject to NVIDIA's license — check its model card before use.