Embodied Semantic Communication for Collective Autonomous Agents: A Tutorial on Representation, Wireless Delivery, and Closed-Loop Coordination

2026-09-28

AI Summary

This study addresses the collaboration incompatibility among heterogeneous agents in dynamic physical environments caused by neglecting state evolution, pioneering an embodied semantic communication paradigm. By integrating semantic information theory, world models, and multi-agent decision theory, this approach transcends conventional bit-level transmission limitations, transforming communication into action-oriented interaction. Perception and intent are encapsulated as executable representations, enabling unified semantic alignment of multimodal states and hardware capabilities for closed-loop coordination. Furthermore, this work delineates system boundaries and proposes a roadmap encompassing bandwidth-adaptive mechanisms and ambiguity-triggered interactions. Ultimately, it provides critical technical foundations for advancing collective embodied networks.

Abstract

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.

Problem

• Embodied Semantic Communication
• Multi-agent Collaboration
• Heterogeneous Agents
• Action-oriented Semantics
• Collective Autonomous Agents

Innovation

• Embodied Semantic Communication
• Actionable Semantic Representation
• Multi-Agent Coordination
• World Models
• Semantic Information Theory