In recent years, the need for resources for handling processes with high computational complexity for mobile robots is becoming increasingly urgent. More specifically, robots need to autonomously operate in a robust and continuous manner, while keeping high performance, a need that led to the utilization of edge computing to offload many computationally demanding and time-critical robotic procedures. However, safe mechanisms should be implemented to handle situations when it is not possible to use the offloaded procedures, such as if the communication is challenged or the edge cluster is not available. To this end, this article presents a switching strategy for safety, redundancy, and optimized behavior through an edge computing-based Model Predictive Controller (MPC) and a low-level onboard-PID controller for edge-connected Unmanned Aerial Vehicles (UAVs). The switching strategy is based on the communication Key Performance Indicators (KPIs) over 5G to decide whether the UAV should be controlled by the edge-based or have a safe fallback based on the onboard controller.

翻译：近年来，移动机器人处理高复杂度计算任务所需的资源需求日益迫切。具体而言，机器人需要以鲁棒且持续的方式自主运行，同时保持高性能——这一需求催生了利用边缘计算来卸载大量计算密集型且时间关键的机器人流程。然而，当无法使用卸载流程时（例如通信受阻或边缘集群不可用），应实施安全机制。为此，本文提出一种通过边缘计算模型预测控制器与低层级机载PID控制器相结合实现安全性、冗余性和优化行为的切换策略，该策略面向边缘连接无人机。切换方案基于5G通信关键性能指标，用于决策无人机应由边缘控制器控制，还是通过机载控制器实现安全回退。