The fifth generation (5G) cellular network technology is mature and increasingly utilized in many industrial and robotics applications, while an important functionality is the advanced Quality of Service (QoS) features. Despite the prevalence of 5G QoS discussions in the related literature, there is a notable absence of real-life implementations and studies concerning their application in time-critical robotics scenarios. This article considers the operation of time-critical applications for 5G-enabled unmanned aerial vehicles (UAVs) and how their operation can be improved by the possibility to dynamically switch between QoS data flows with different priorities. As such, we introduce a robotics oriented analysis on the impact of the 5G QoS functionality on the performance of 5G-enabled UAVs. Furthermore, we introduce a novel framework for the dynamic selection of distinct 5G QoS data flows that is autonomously managed by the 5G-enabled UAV. This problem is addressed in a novel feedback loop fashion utilizing a probabilistic finite state machine (PFSM). Finally, the efficacy of the proposed scheme is experimentally validated with a 5G-enabled UAV in a real-world 5G stand-alone (SA) network.

翻译：第五代（5G）蜂窝网络技术已趋成熟，并在众多工业及机器人应用中得到日益广泛的部署，其中高级服务质量（QoS）功能尤为关键。尽管相关文献中5G QoS讨论已较为普遍，但在时间关键型机器人场景中针对其实际应用的真实实现及研究仍显著匮乏。本文探讨了5G赋能的无人机（UAV）在运行时间关键型应用时的性能表现，以及通过动态切换不同优先级的QoS数据流来优化其运行的可能性。为此，我们提出了一种面向机器人的分析框架，系统评估5G QoS功能对5G赋能无人机性能的影响。此外，我们提出了一种新型动态选择不同5G QoS数据流的框架，该框架由5G赋能无人机自主管理。该问题通过一种采用概率有限状态机（PFSM）的新型闭环反馈机制加以解决。最终，我们利用真实5G独立组网（SA）网络中的5G赋能无人机对所提方案的有效性进行了实验验证。