6G需从通信平台转向支持智能体物理行为的闭环系统
Empowering Embodied AI in 6G Networks: Architecture, Enablers, and Open Challenges
- 构建感知-通信-行动一体化架构，实现物理环境闭环控制
- 强调通信性能直接影响机器人等智能体的任务成功率与稳定性
- 适合关注6G与机器人/自动驾驶融合的科研与工程人员
具身人工智能正成为6G无线网络的关键驱动力，使机器人、自动驾驶车辆及扩展现实（XR）设备等智能体能在动态物理环境中持续感知、通信并执行动作。与传统处理离散数据的AI系统不同，具身智能体通过感知-通信-行动（PCA）闭环交互运行，其通信性能直接决定物理行为表现、控制稳定性和任务完成度。然而，现有以连接为中心的AI原生无线架构难以大规模支撑任务驱动的具身智能。为此，本文提出一个面向具身AI的6G系统整体框架，将通信、感知、计算与控制协同设计为统一闭环基础设施。我们阐述了系统级PCA架构，讨论关键技术与典型应用，并指出多模态智能、边缘感知部署、评估体系、可信性及实际落地等核心挑战。核心观点是：未来6G必须从智能通信平台演进为具身物理智能的主动赋能者。
原文摘要 · Abstract (English)
Embodied artificial intelligence (AI) is emerging as a key driver of the sixth-generation (6G) wireless networks by enabling agents that continuously perceive, communicate, and act in dynamic physical environments. Unlike conventional AI systems that process disembodied data, embodied agents such as robots, autonomous vehicles, and extended reality (XR) devices operate through closed-loop perception-communication-action (PCA) interactions, where communication performance directly affects physical behavior, control stability, and task success. However, existing AI-native wireless architectures remain largely connectivity-centric and are not designed to support task-driven embodied intelligence at large scale. Therefore, we present a holistic framework for embodied AI-native 6G systems, in which communication, sensing, computation, and control are jointly designed as a unified closed-loop infrastructure. We introduce a system-level PCA architecture, discuss key enabling technologies and representative applications, and highlight major open challenges in multimodal intelligence, edge-aware deployment, evaluation, trustworthiness, and practical implementation. Our central argument is that future 6G systems must evolve from intelligent communication platforms into active enablers of embodied physical intelligence.
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