发表机构
Northwestern Polytechnical University; Xi’an Jiaotong University; Xidian University; University of Houston（西北工业大学; 西安交通大学; 西安电子科技大学; 休斯顿大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出具身语义通信范式，将多模态感知与协作意图封装为可行动语义表示，使异构智能体在动态环境中形成协调行动，并梳理了关键技术挑战与路线图。
AI 中文摘要
随着自主系统和具身智能进入动态物理世界，多智能体协作要求通信设计发生范式转变。然而，现有通信范式忽视了智能体通过一个随任务展开而演化的过程，从自身状态、环境观测和协作关系中形成行动理解。因此，仅靠可靠的比特传输、通用的语义恢复或单一任务效用优化，无法确保异构智能体在任务执行过程中，从共享信息中形成与其自身条件相协调的行动。为解决这一缺口，本文提出具身语义通信（ESC）作为一种范式，将信息传输转变为面向行动（action-oriented）的语义交互。具体而言，ESC刻画了显式通信链路如何将多模态感知状态、内在硬件能力和协作意图封装为统一的可行动语义表示，从而使异构接收智能体能够在本地运动控制中对其进行解析、对齐和落地。本文阐明了ESC的概念边界、系统特性和环境受限的技术路径，并映射了其底层数学工具，包括语义信息论、世界模型和多智能体决策理论。最后，本文总结了关键开放挑战，包括可测量的语义可靠性、动态环境和任务下由歧义触发的交互，以及带宽自适应的语义传输，并为集体具身网络勾勒了发展路线图。
英文摘要
As autonomous systems and embodied intelligence enter the dynamic physical world, multi-agent collaboration calls for a paradigm shift in communication design. However, existing communication paradigms overlook that agents form action understanding from their own states, environmental observations, and collaboration relations through a process that evolves as a task unfolds. Consequently, reliable bit delivery, general semantic recovery, or single-task utility optimization alone cannot ensure that heterogeneous agents form coordinated actions compatible with their own conditions from shared information during task execution. To address this gap, this paper proposes embodied semantic communication (ESC) as a paradigm that transforms information transmission into action-oriented semantic interaction. Specifically, ESC characterizes how an explicit communication link can encapsulate multimodal perceptual states, intrinsic hardware capabilities, and collaborative intents into unified actionable semantic representations, thereby enabling heterogeneous receiving agents to parse, align, and ground them in local motor control. This paper clarifies the conceptual boundary, system characteristics, and environment-constrained technical pathways of ESC. It maps the underlying mathematical tools, including semantic information theory, world models, and multi-agent decision theory. Finally, this paper summarizes key open challenges, including measurable semantic reliability, ambiguity-triggered interaction under dynamic environments and tasks, and bandwidth-adaptive semantic transmission, outlining a roadmap for collective embodied networks.
