RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaboration

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 cross-embodiment and multi-agent collaboration Framework for 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.