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A Brain-inspired Hierarchical Framework for Zero-Shot Robot Task Reasoning and Execution

arXiv · AI, language, vision and robotics · article · Sep 5, 2026 · UTC

Robots that follow open-ended language instructions need to connect semantic intent to visual scene understanding, geometric feasibility, object states, and physical interaction conditions. End-to-end Vision-Language-Action policies have improved cross-task generalization, but they typically map visual and language inputs directly to robot actions, leaving limited explicit structure for long-horizon decomposition, physical verification, and recovery. We present \method, a zero-shot hierarchical framework functionally inspired by the division of roles in the human brain, comprising visual perce

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