Autonomous flight for UAVs relies on visual information for avoiding obstacles and ensuring safe collision-free flight. In addition to visual clues, safe UAVs often need connectivity with the ground station. In this article, 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 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.

中文翻译：

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无人机的边缘计算辅助自动飞行：视觉与通信之间的协同作用

无人机的自主飞行依靠视觉信息来避免障碍物并确保安全的无碰撞飞行。除了视觉提示外，安全的无人机通常还需要与地面站建立连接。在本文中，我们研究了启用边缘计算的无人机飞行的视觉与通信之间的协同作用。通过提出边缘计算辅助自主飞行（ECAAF）的框架，我们说明了视觉和通信可以在边缘计算和卸载的帮助下相互作用并互相帮助，并进一步加快了无人机任务的完成速度。ECAAF由三个功能组成，详细讨论这些功能：用于3D地图获取的边缘计算，从3D地图构建无线电地图以及在线轨迹规划。在ECAAF期间，通信能力，视频卸载，3D地图质量，轨迹的通道状态形成正反馈回路。仿真结果验证了所提方法能够通过增强连通性来提高任务性能。最后，我们总结了一些未来的研究方向。