Digital Twin-Based 6G Testbed for Immersive Outdoor Robotics: Capacity and Latency Analysis of the Interaction with Real and Virtual Objects

This paper presents an experimental Digital Twin platform developed as a Beyond 5G testbed for immersive remote and autonomous driving applications for mobile robots. The testbed, deployed in UPV facilities, integrates use cases involving the immersive and cyber-physical remote driving of mobile robots, which interact with real and virtual objects. In this controlled environment, we study the capacity and latency requirements of future autonomous driving use cases based on sensor offloading to the Edge. Our study focuses on evaluating the influence of 5 G communication across multiple latency sources, including video streaming, AI-assisted perception, and telecontrol. By identifying key bottlenecks in mobile robot teleoperation, this work provides insights into the latency constraints that must be addressed by future 6 G networks to enable the largescale deployment of autonomous driving across different industry verticals. The results show that, while the bottleneck of the system are the robot's motors (up to 589.65 ms), the 360 video latency (up to 433.3 ms) and the telecontrol latency ($\mathbf{1 2 2. 5 ~ m s}$) could be improved by network enhancements.