arXiv cs.MA· Jiahe Guo, Jun Du, Chunxiao Jiang, Jintao Wang·· 9 天前AI 评分15
面向协作 ISAC 的基于 Token 通信的具身多智能体框架
An Embodied Multiagent Framework Based on Token Communications for Cooperative ISAC
AI 导读
该论文提出 SI-TokCom 框架，用多智能体具身策略学习驱动无人机具身智能体的 Token 通信与物理控制联合优化，以在满足通信与感知速率要求下最小化总推进能耗。仿真显示其通信与感知速率分别达到集中式基线的 98.9% 和 99.1%，相比本地基线提升 5.0% 和 43.6%，推进能耗基本不变。
正文 · 原文
Abstract:The emerging low-altitude economy demands unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) for reliable connectivity and environmental awareness. In particular, embodied UAV agents offer a promising means of supporting autonomous operations through a closed loop linking perception, decision-making, and physical actions. However, each UAV has access only to local observations, and effective cooperation requires exchanging local states and intentions. Directly sharing such information can incur substantial signaling overhead and hinder timely coordination in dynamic environments. To deal with this problem, this paper investigates a cooperative ISAC network of embodied UAV agents and formulates a joint token communications (TokCom) and physical control problem to minimize total propulsion energy subject to communication and sensing rate requirements. Then, we propose a state--intent TokCom (SI-TokCom) framework driven by multi-agent embodied policy learning. Specifically, separate pretrained codebooks enable compact exchanges of local states and intentions, while UAV agents jointly learn to select and compose tokens and determine physical actions based on local observations and received tokens. Simulation results show that SI-TokCom achieves 98.9\% and 99.1\% of the centralized baseline's communication and sensing rates, respectively. Compared with the local baseline, it improves the corresponding rates by 5.0\% and 43.6\%, respectively, with essentially unchanged propulsion energy. These results highlight the potential of TokCom for communication-efficient cooperation among embodied UAV agents in ISAC systems.
| Comments: | Submitted to TWC |
| Subjects: | Signal Processing (eess.SP); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2610.11434 [eess.SP] |
| (or arXiv:2610.11434v1 [eess.SP] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11434 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Jiahe Guo [view email]
[v1]
Thu, 8 Oct 2026 07:56:55 UTC (3,901 KB)
来源：arXiv cs.MA · arxiv.org