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Daxiao proposes dual-brain collaboration architecture, exploring robot experience reuse

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Daxiao proposes a "dual-brain collaboration" architecture that connects the cloud brain SenseNova's task understanding and planning capabilities with the on-device Kaiwu world model's physical state judgment and action-consequence prediction, organized by an embodied Harness for perception, memory, skills, and control. The architecture aims to retain a single robot's interaction experience, along with evidence and applicable conditions, for other robots to reuse across tasks, scenarios, and embodiments, reducing repeated trial and error. The system is organized around three progressive loops: autonomous execution, experience learning, and recursive self-improvement. Daxiao says this exploration is still at an exploratory stage and has not yet provided real-machine validation metrics.

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11月6日
  1. 未来机器人网 · 微信公众号
    Daxiao explores dual-brain collaboration: from real interaction to reusable physical experience

    Daxiao proposes a "dual-brain collaboration" architecture that connects the cloud brain SenseNova's task understanding and planning capabilities with the on-device Kaiwu world model's judgment of physical states and prediction of action consequences, while an embodied Harness organizes perception, memory, skills, and control. The exploration aims to preserve a single robot's interaction experience, along with evidence and applicable conditions, so that other robots can reuse it across tasks, scenarios, and embodiments, reducing repeated trial and error. The system is organized around three progressive loops: autonomous execution, experience learning, and recursive self-improvement. It is currently at the exploration stage and has not yet provided real-machine validation metrics.

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