arXiv Computer Vision By Pengfei Zhou, Yixing Ma, Zhengfeiyang Zhang, Haoyuan Chen, Zhenglin Wan, Hexin Wang, Wangbo Zhao, Yang You

REA: A Routed Embodied Agent Runtime for Asynchronous Brain-Cerebellum Control

Read the original on arXiv Computer Vision →

The paper introduces REA, a unified runtime that integrates a deliberative foundation model (System 2), an embodied router (System 1), and fast reactive policies (System 0) for embodied agents. REA avoids blocking fast execution by using a route memory, a judge gate, and a shared‑budget escalation ladder, enabling asynchronous coordination between the brain and reflexes. Experiments on LIBERO‑Pro, RoboTwin 2.0, BEHAVIOR‑1K, and a real Unitree G1 humanoid show that REA achieves higher success rates and reduces control steps and time compared to single‑policy baselines.

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