  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.
