Rethinking Networked Robotics in the 6G Era With Generative AI-in-the-Loop

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Abstract
Networked robotics continues to be a key component of various industrial systems. 6G will empower networked robotics with the envisaged capabilities like hyper-reliable and low-latency connectivity and in-network intelligence. While communication and control techniques have been widely investigated; co-design and AI-based solutions for autonomy and reasoning are still emerging. In this article, we propose a generative Al-in-the-Loop (GITL) framework for the control and coordination of networked robotic systems. The generative AI (GAI) agent oversees three interrelated loops: the communication loop, the robot control loop, and the Al model control loop, making holistic decisions by interpreting task requirements, network status, and robotic operations. Acting as a high-level cross-domain coordinator, the GAI agent leverages background knowledge of AI models, robot behaviors, and network policies, ensuring seamless interplay across different operational scenarios. This approach ultimately enables a highly autonomous networked robotic system capable of handling complex tasks with minimal human intervention. We anticipate that the GITL paradigm will play a pivotal role in unlocking the full potential of networked robotic systems, enabling enhanced autonomy, adaptability, and coordination in the emerging 6G and Industry 5.0 era.
Funding Information
  • 6G-GOALS Project through the 6G SNS-JU Horizon Program (101139232)

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