构建5G/6G开放无线网络测试平台,实现工业机器人边缘AI服务
End-to-End O-RAN Testbed for Edge-AI-Enabled 5G/6G Connected Industrial Robotics
- 基于O-RAN开放架构搭建端到端测试平台,支持边缘AI服务
- 实测验证不同感知数据处理方案在实时性上的性能差异
- 适合研究6G智能工厂、边缘计算与机器人协同的科研人员
连接式机器人是推动6G移动通信网络向更智能方向演进的关键应用场景。通过用高可靠、高吞吐、低延迟的5G/6G无线接口替代有线连接,可实现机器人系统的移动性,并将计算密集型的人工智能(AI)模型如感知与控制任务卸载至网络边缘服务器。向边缘AI即服务(E-AIaaS)转型,简化了工业环境中机器人的现场维护,降低运营成本,同时支持灵活的AI模型生命周期管理与功能持续升级。本文提出一个基于5G/6G O-RAN的端到端测试平台,集成面向工业机器人应用的E-AIaaS。目标是设计并部署一个基于开放技术与接口的通用实验平台,通过一个自主焊接场景进行示范。在此场景中,测试平台用于研究不同数据采集、边缘处理和实时流传输方法在机器人感知中的权衡关系,同时支持语义通信、目标导向通信等新兴范式。
原文摘要 · Abstract (English)
Connected robotics is one of the principal use cases driving the transition towards more intelligent and capable 6G mobile cellular networks. Replacing wired connections with highly reliable, high-throughput, and low-latency 5G/6G radio interfaces enables robotic system mobility and the offloading of compute-intensive artificial intelligence (AI) models for robotic perception and control to servers located at the network edge. The transition towards Edge AI as a Service (E-AIaaS) simplifies on-site maintenance of robotic systems and reduces operational costs in industrial environments, while supporting flexible AI model life-cycle management and seamless upgrades of robotic functionalities over time. In this paper, we present a 5G/6G O-RAN-based end-to-end testbed that integrates E-AIaaS for connected industrial robotic applications. The objective is to design and deploy a generic experimental platform based on open technologies and interfaces, demonstrated through an E-AIaaS-enabled autonomous welding scenario. Within this scenario, the testbed is used to investigate trade-offs among different data acquisition, edge processing, and real-time streaming approaches for robotic perception, while supporting emerging paradigms such as semantic and goal-oriented communications.
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