End-to-End O-RAN Testbed for Edge-AI-Enabled 5G/6G Connected Industrial Robotics

TL;DR

This paper presents an end-to-end 5G/6G O-RAN testbed integrating Edge AI for industrial robotics, enabling flexible, low-latency robotic control and perception with open technology interfaces.

Contribution

It introduces a novel open-technology-based testbed for Edge AI-enabled industrial robotics, demonstrating its application in an autonomous welding scenario.

Findings

Trade-offs in data acquisition and edge processing methods

Support for semantic and goal-oriented communications

Effective integration of E-AIaaS in industrial robotics

Abstract

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.