Unverified50% confidenceFactExact time
The Pilot paper proposes a unified single-stage reinforcement learning framework for Local Manipulation of humanoid robots in unstructured scenarios, including a cross-modal context encoder and a MoE policy architecture; experiments were conducted in simulation environments and on a 29-degree-of-freedom Unitree G1 physical robot, and the paper claims it outperforms baseline methods in stability, instruction tracking, and terrain traversability.
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10/14/2026
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