Dynamic Distributed Computing for Infrastructure-Assisted Autonomous UAVs

The analysis of information rich signals is at the core of autonomy. In airborne devices such as Unmanned Aerial Vehicles (UAV), the hardware limitations imposed by the weight constraints make the continuous execution of these algorithms challenging. Edge computing can mitigate such limitations and boost the system and mission performance of the UAVs. However, due to the UAVs motion characteristics and complex dynamics of urban environments, remote processing-control loops can quickly degrade. This paper presents Hydra, a framework for the dynamic selection of communication/computation resources in this challenging environment. A full - open-source - implementation of Hydra is discussed and tested via real-world experiments.