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RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World

📝Paper | 🌍Project Page | 🛢️Data

eight_skills

Release

  • [2024/12/04] We have released the RoboMatrix supervised fine-tuning (SFT) dataset, which contains 1,500 high-quality human-annotated demonstration videos.

Demo

Dynamic Adversarial Interaction

crossing_obstacles_with_adversarial_interaction.mp4

🛠️ Installation

1. Install ROS 2

Note: If ROS2 is already installed on your system, please skip this step.

ROS2 distro for your Ubuntu

Install colcon tool

sudo apt install python3-colcon-common-extensions

2. Build workspace

mkdir -p ~/RoboMatrix/src && cd ~/RoboMatrix/src
git clone https://github.com/WayneMao/RoboMatrix.git
cd ~/RoboMatrix && colcon build

3. Install dependencies

sudo apt install libopus-dev python3-pip
python3 -m pip install -U numpy numpy-quaternion pyyaml

# Install RoboMaster-SDK
python3 -m pip install git+https://github.com/jeguzzi/RoboMaster-SDK.git
python3 -m pip install git+https://github.com/jeguzzi/RoboMaster-SDK.git#"egg=libmedia_codec&subdirectory=lib/libmedia_codec"

# install dependencies and torch
pip install -r requirements.txt
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118

4. Third party

Grounding-DINO-1.5-API

cd src/robomatrix_client/robomatrix_client
git clone https://github.com/IDEA-Research/Grounding-DINO-1.5-API.git
cd Grounding-DINO-1.5-API
pip install -v -e .

Deployment on Real-Robots

TODO

  • Package Docker
  • 🤗 Release Supervised Fine-tuning dataset
  • Optimize VLA ROS communication
  • Open source VLA Skill model code
  • Release VLA Skill model weights
  • Open source Shooting code

Citation

If you find our work helpful, please cite us:

@article{mao2024robomatrix,
  title={RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World},
  author={Mao, Weixin and Zhong, Weiheng and Jiang, Zhou and Fang, Dong and Zhang, Zhongyue and Lan, Zihan and Jia, Fan and Wang, Tiancai and Fan, Haoqiang and Yoshie, Osamu},
  journal={arXiv preprint arXiv:2412.00171},
  year={2024}
}

Acknowledgments


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