Embodied AI in 6G Networks: From Intelligent Connectivity to Physical Intelligence
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Abstract (arXiv)
Embodied artificial intelligence (AI) couples perception and learned decision making to actions that change the physical world. This coupling distinguishes an embodied agent from a conventional connected controller: the agent maintains task state and uncertainty, reasons about the consequences of actions, and adapts from subsequent observations. Wireless networking becomes relevant when perception, inference, or coordination is distributed, but it should not replace local safety control. This article develops a tutorial perception--communication--action (PCA) architecture that exposes task state, action deadlines, uncertainty, agent intent, and safety envelopes to a 6G orchestration plane. It separates capabilities already addressed by 5G and 5G-Advanced from functions that motivate 6G, including task-state interfaces, semantic freshness, predictive digital twins, and safety-aware coordination across agents. A multi-robot simulation study is retained to illustrate joint sensing, communication, and computation control. The results show where network orchestration improves task utility and where local autonomy remains essential.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 15 references that are in the map. First posted on arXiv 17 May 2026.
Builds on
6 of 15 references.
References · 6
- 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 942
- 2020Deep Learning Enabled Semantic Communication Systemscited by 292
- 2020V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Predictioncited by 292
- 2021A Survey of Embodied AI: From Simulators to Research Taskscited by 261
- 2018Wireless Network Intelligence at the Edgecited by 92
- 2021Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyondcited by 91
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Citing papers per year: 2026: 2.
2 papers.