RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration
⭐️ Project (Coming soon) │ 🌎 Demo (Coming soon) │ 📑 Technical Report
🤖 RoboBrain 2.0: Advanced version of RoboBrain. See Better. Think Harder. Do Smarter.
🤖 RoboBrain 1.0: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete.
The rise of embodied intelligence has intensified the need for robust multi-agent collaboration in industrial automation, service robotics, and smart manufacturing. However, current robotic systems struggle with critical limitations, including poor cross-embodiment adaptability, inefficient task scheduling, and inadequate dynamic error correction. While end-to-end vision-language-action (VLA) models (e.g., OpenVLA, RDT, Pi-0) exhibit weak long-horizon planning and task generalization, hierarchical VLA models (e.g., Helix, Gemini-Robotics, GR00T-N1) lack cross-embodiment compatibility and multi-agent coordination capabilities. To address these challenges, we present RoboOS, the first open-source embodied operating system based on a Brain-Cerebellum hierarchical architecture, facilitating a paradigm shift from single-agent to swarm intelligence. Specifically, RoboOS comprises three key components: (1) the Embodied Cloud Model, a multimodal large language model (MLLM) for global perception and high-level decision-making; (2) the Cerebellum Skill Library, a modular, plug-and-play toolkit for seamless multi-skill execution; and (3) Real-Time Shared Memory, a spatiotemporal synchronization mechanism for multi-agent state coordination. By integrating hierarchical information flow, RoboOS bridges the Embodied Brain and Cerebellum Skill Library, enabling robust planning, scheduling, and error correction for long-horizon tasks while ensuring efficient multi-agent collaboration by Real-Time Shared Memory. Moreover, we optimize edge-cloud communication and cloud-based distributed inference to support high-frequency interactions and scalable deployment. Extensive real-world experiments across diverse scenarios (e.g., restaurant, household, supermarket) demonstrate RoboOS’s versatility, supporting heterogeneous embodiments (single-arm, dual-arm, humanoid, wheeled), which provides a scalable and practical solution for cross-embodiment collaboration, pushing the boundaries of embodied intelligence.
- Release RoboOS-1.0 version
- Release Technical Report of RoboOS.
- Release RoboOS-2.0 version (by the end of this month)
- Release friendly and detailed User Guide Manual.
- Release more comprehensive multi-agent collaboration DEMOs based on RoboOS.
Coming soon ...
Due to the substantial code refactoring and engineering efforts required, we'll need to postpone the release by several days. We appreciate your patience as we ensure the highest quality standards.
- Python 3.8+
- Redis server
- pip package manager
# Clone the repository
git clone https://github.com/FlagOpen/RoboOS.git
cd RoboOS
# Install dependencies
pip install -r requirements.txt
# 1. Start Redis
redis-server
# 2. Start Master
python master/run.py
# 3. Start Slaver (for multi-agent, your should run at different robots respectively)
python slaver/run.py
# 4. Launch Web Interface
python gradio_ui.py
# Then, access the web interface at: http://localhost:7861
If you find this project useful, welcome to cite us.
@article{tan2025roboos,
title={RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration},
author={Tan, Huajie and Hao, Xiaoshuai and Lin, Minglan and Wang, Pengwei and Lyu, Yaoxu and Cao, Mingyu and Wang, Zhongyuan and Zhang, Shanghang},
journal={arXiv preprint arXiv:2505.03673},
year={2025}
}
@article{ji2025robobrain,
title={RoboBrain: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete},
author={Ji, Yuheng and Tan, Huajie and Shi, Jiayu and Hao, Xiaoshuai and Zhang, Yuan and Zhang, Hengyuan and Wang, Pengwei and Zhao, Mengdi and Mu, Yao and An, Pengju and others},
journal={arXiv preprint arXiv:2502.21257},
year={2025}
}
