智源 FlagOpen 开源 RoboOS：面向跨本体与多机器人协作的具身操作系统
GitHub - FlagOpen/RoboOS: 🤖 RoboOS: A Universal Embodied Operating System for Cross-Embodied and Multi-Robot Collaboration · GitHub
智源 FlagOpen 开源 RoboOS，这是首个基于“大脑-小脑”分层架构的开源具身操作系统，包含具身云模型（MLLM）、小脑技能库和实时共享内存三大组件，支持单臂、双臂、人形、轮式等异构本体协作。项目已发布 RoboOS-1.0 与技术报告，RoboOS-2.0 计划于本月底发布，并采用 SaaS + MCP 结构，支持轻量单机部署。
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FlagOpen; RoboOS
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README; Apache-2.0 license
⭐️ Project │ 🌎 Demo │ 📑 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.
Please visit the stone-alone branch for RoboOS version 2.0, which supports lightweight single-machine deployment!
🔥 Overview
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.
Structure for RoboOS 2.0 (SaaS + MCP)
Structure for RoboOS 1.0
🎯 RoadMap
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
⭐️ Full Guide Manual (RoboOS-2.0)
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.
⭐️ Simple Guide Manual (Only for RoboOS-1.0)
1. Prerequisites
Python 3.8+; Redis server; pip package manager
📑 Citation
If you find this project useful, welcome to cite us.