系统梳理具身AGI五层框架，指明从感知到自主决策的进化路径。
Toward Embodied AGI: A Review of Embodied AI and the Road Ahead
- 提出具身AGI五级分类体系，从基础感知到高级认知分层
- 分析当前研究在感知与动作层面的瓶颈与进展
- 构建面向高阶能力的机器人脑概念框架，适合智能体研发者参考
通用人工智能（AGI）常被设想为具有身体的形态。随着机器人技术和基础大模型的快速发展，我们正站在一个新时代的门槛上——具身人工智能系统将日益具备泛化能力。本文通过引入一个涵盖五个层级（L1-L5）的具身AGI系统性分类框架，推动该领域的讨论。我们回顾了基础层级（L1-L2）的研究现状与挑战，并阐明实现更高层级能力（L3-L5）所需的关键组件。基于这些洞察与现有技术，本文提出一个面向L3+机器人的概念性大脑框架，不仅提供技术展望，也为未来探索奠定基础。
原文摘要 · Abstract (English)
Artificial General Intelligence (AGI) is often envisioned as inherently embodied. With recent advances in robotics and foundational AI models, we stand at the threshold of a new era-one marked by increasingly generalized embodied AI systems. This paper contributes to the discourse by introducing a systematic taxonomy of Embodied AGI spanning five levels (L1-L5). We review existing research and challenges at the foundational stages (L1-L2) and outline the key components required to achieve higher-level capabilities (L3-L5). Building on these insights and existing technologies, we propose a conceptual framework for an L3+ robotic brain, offering both a technical outlook and a foundation for future exploration.
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