RoboOS - The first cross-ontology embodied cerebellum-cerebellum collaborative framework launched by the Academy of Artificial Intelligence.

What is RoboOS?

RoboOS is the first cross-ontology embodied cerebellum-cerebellum collaborative framework launched by the Beijing Academy of Artificial Intelligence (BAAI). Based on a hierarchical "brain-cerebellum" architecture, the embodied brain RoboBrain is responsible for global perception and decision-making, the cerebellum skill library is responsible for low-latency and precise execution, and the cross-robot data hub shares spatial, temporal, and ontological memories in real time, forming a closed loop of perception-cognition-decision-action. RoboOS supports different types of embodied ontologies such as Songling dual-arm, Ruiman single/dual-arm, Zhiyuan humanoid, and Yushu humanoid, achieving "plug-and-play" integration of brain models and cerebellum skills. Through a shared memory system, it enables state synchronization and intelligent collaboration among multiple robots. RoboOS has integrated edge-cloud collaboration capabilities, supporting edge-cloud collaboration of multiple robot systems, with command response latency of less than 10ms.

Main functions of RoboOS

• Cross-ontology collaborationBased on a hierarchical "brain-cerebellum" architecture, it supports different types of embodied bodies such as Songling dual-arm, Ruiman single/dual-arm, Zhiyuan humanoid, and Yushu humanoid, enabling state synchronization and intelligent collaboration among multiple robots and breaking through the limitations of traditional "information silos".
• Task planning and executionRoboBrain, the embodied brain, is responsible for global perception and decision-making, constructing dynamic spatiotemporal perception, planning guidance, and feedback and error correction mechanisms; the cerebellum skill library is responsible for low-latency and precise execution, achieving flexible and precise operation, forming a closed loop of perception-cognition-decision-action.
• Dynamic task managementIt can dynamically manage multi-robot task queues, support priority preemption and resource optimization allocation, ensure real-time response in complex scenarios, and achieve high-concurrency task scheduling. It can dynamically adjust strategies based on execution feedback, continuously optimize task planning in conjunction with environmental changes, improve robustness, and achieve real-time closed-loop optimization.
• Plug and play and rapid deploymentIt enables "plug-and-play" integration of brain models (such as LLM/VLM) and cerebellar skills (such as grasping and navigation), natively supports flexible integration of heterogeneous robot bodies, and quickly completes robot capability modeling and adaptation using a Profile template mechanism, significantly reducing development threshold and integration costs.
• End-to-end cloud integration and collaborationIn edge deployment, once the robot registers, it can automatically establish a two-way communication link with the RoboBrain brain deployed in the cloud. Through an efficient publish-subscribe mechanism, it can achieve real-time task scheduling and status feedback, with a command response latency of less than 10ms, meeting the closed-loop control requirements of complex dynamic tasks.

RoboOS Technical Principles

• "Brain-Cerebellum" hierarchical structure:
  • RoboBrain: Responsible for overall perception and decision-making, and building dynamic spatiotemporal perception, planning guidance and feedback error correction mechanisms.
  • Cerebellum Skill Library: Responsible for low-latency and precise execution, enabling flexible and precise operation, etc.
  • Cross-robot data hubIt is responsible for sharing spatial, temporal, and ontological memories in real time, providing information support for decision-making, planning, and optimized collaborative operations, thereby forming a closed loop of perception-cognition-decision-action.

Application scenarios of RoboOS

• Industrial AutomationIn industrial production, RoboOS enables collaboration between different types of robots to complete complex production tasks, such as multiple robots working together to handle and assemble parts, thereby improving production efficiency and quality.
• Smart LogisticsRoboOS enables logistics robots to collaborate in warehousing and distribution processes, such as sorting, handling, and delivering goods, thereby optimizing logistics workflows.
• Smart manufacturingIn the field of smart manufacturing, RoboOS can be used to automate complex manufacturing tasks, improving the flexibility and adaptability of production.
• service robotsRoboOS can be used for service robots in different scenarios, such as restaurant service and hotel service, to enable collaboration between robots and provide more efficient services.
• Laboratory and Scientific ResearchRoboOS provides researchers with a powerful platform for studying cutting-edge technologies such as autonomous mobile robots and self-driving cars.