令牌通信辅助的协作具身人工智能：概念、框架与机遇
Token Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunities
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中文总结 AI 辅助
本文提出令牌通信辅助的协作具身人工智能框架，利用令牌作为语义载体和推理单元，通过任务自适应协议降低通信开销，同时保持任务效率与鲁棒性。
中文摘要 AI 辅助
协作具身人工智能（CEAI）使多个物理智能体能够在动态环境中协同感知、推理和行动。有效通信对CEAI至关重要，然而CEAI智能体不仅需要交换大规模多模态观测数据，还需在长时间跨度内交换与任务相关的见解、意图和交互信息。本文研究令牌通信（TokCom）作为CEAI的原生智能接口，其中令牌同时作为通信的紧凑语义载体和生成式基础模型（GFMs）的基本推理单元。我们首先讨论TokCom如何支持具身智能体之间的见解共享、意图对齐和交互控制。然后，我们提出一个由任务自适应通信协议驱动的TokCom辅助CEAI框架。该协议由紧凑码本、语法规则和上下文示例组成，指导基于GFM的收发器将消息蒸馏为紧凑令牌，并在无线传输后重建它们。一个关于协作物体搬运的案例研究表明，所提出的TokCom框架在保持任务效率并在噪声信道下展现鲁棒性的同时，大幅降低了源负载比特消耗。最后，我们概述了未来的研究方向。
英文摘要
Collaborative embodied artificial intelligence (CEAI) enables multiple physical agents to perceive, reason, and act cooperatively in dynamic environments. Effective communication is essential for CEAI, yet CEAI agents must exchange not only large multimodal observations but also task-relevant insights, intents, and interactive information over long horizons. This article investigates token communication (TokCom) as a native intelligence interface for CEAI, in which tokens serve jointly as compact semantic carriers for communication and fundamental inference units for generative foundation models (GFMs). We first discuss how TokCom supports insight sharing, intent alignment, and interactive control among embodied agents. We then propose a TokCom-assisted CEAI framework driven by a task-adaptive communication protocol. Comprising a compact codebook, syntax rules, and contextual examples, this protocol guides GFM-based transceivers to distill messages into compact tokens and reconstruct them after wireless transmission. A case study on collaborative object transport demonstrates that the proposed TokCom framework substantially reduces the source payload bit consumption while preserving task efficiency and showing robustness under noisy channels. Finally, we outline future research directions.
发表机构
- University of Electronic Science and Technology of China（电子科技大学）
机构由 AI 辅助整理，请以论文原文为准。
