Galaxy Star Brain Enables Real Robot Deployment

• Galaxy Star Brain AstraBrain Architecture: Integrates brain, cerebellum, and neural control into unified system enabling autonomous decision-making without pre-programming[1] • Training Pipeline: Four-stage approach combining human few-shot demonstrations, massive virtual world simulations, billions of reinforcement learning iterations, and targeted real-world data fine-tuning[1] • Hardware Optimization: External panda shell required dynamic model recalibration due to center-of-gravity distribution changes; thermal management achieved through current management and power control to prevent joint module overheating[1] • Synchronization Protocol: Millisecond-level coordination of 100+ robots through unified command encoding with individual machine decoding execution[1] • Embodied AI Paradigm: Multi-layer architecture comprising hardware body (movement), algorithmic brain (cognition), environmental perception (sensing and proprioception), and commercial operation/maintenance (real-world viability)[4] • Vision-Language-Action Models: Integration of visual perception, semantic understanding, and task decomposition enabling reduced human-machine interaction threshold[4] • World Action Models (WAM): Robots simulate physical evolution in internal imagination space before execution; Ctrl-World model (Tsinghua/Stanford) achieves 44.7% average improvement in task success rates using zero real-machine data[4]

Galaxy General's successful deployment of autonomous robots at the Spring Festival Gala signals a critical industry inflection point: the transition from pre-programmed robotic systems to genuinely autonomous embodied AI agents capable of real-time decision-making in unpredictable environments. This achievement validates the end-to-end embodied large model approach as viable for production deployment, contrasting with traditional modular robotics architectures. The ability to coordinate 100+ robots with millisecond-level synchronization while maintaining autonomous operation suggests scalability potential for large-scale industrial and service applications. Convergence of embodied AI, Vision-Language-Action models, and World Action Models indicates that future robot deployment will prioritize generalization and zero-shot task transfer over task-specific programming. Competitors like IntBot (humanoid concierge services) and emerging World Model approaches demonstrate parallel validation of this paradigm. The industry trajectory suggests rapid expansion from entertainment/demonstration contexts into logistics, manufacturing, hospitality, and emergency response domains within 12-24 months, with embodied AI becoming the dominant architecture for autonomous systems.