  Autonomous flight for UAVs relies on visual information for avoiding
obstacles and ensuring a safe collision-free flight. In addition to visual
clues, safe UAVs often need connectivity with the ground station. In this
paper, we study the synergies between vision and communications for edge
computing-enabled UAV flight. By proposing a framework of Edge Computing
Assisted Autonomous Flight (ECAAF), we illustrate that vision and
communications can interact with and assist each other with the aid of edge
computing and offloading, and further speed up the UAV mission completion.
ECAAF consists of three functionalities that are discussed in detail: edge
computing for 3D map acquisition, radio map construction from the 3D map, and
online trajectory planning. During ECAAF, the interactions of communication
capacity, video offloading, 3D map quality, and channel state of the trajectory
form a positive feedback loop. Simulation results verify that the proposed
method can improve mission performance by enhancing connectivity. Finally, we
conclude with some future research directions.
