Paper Info
Title
Edge Computing Assisted Autonomous Flight for UAV: Synergies between Vision and Communications
Abstract
AbstractAutonomous 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.
Year
DOI
Venue
2021
10.1109/MCOM.001.2000501
Periodicals
Keywords
DocType
Volume
edge-computing-enabled UAV flight,ECAAF,UAV mission completion,3D map acquisition,communication capacity,3D map quality,edge computing assisted autonomous flight,visual information,safe collision-free flight,visual clues,safe UAVs,radio map construction,online trajectory planning,video offloading,obstacle avoidance,positive feedback loop
Journal
59
Issue
ISSN
Citations 
1
0163-6804
2
PageRank 
References 
Authors
0.38
0
6
Name
Order
Citations
PageRank
Quan Chen120.38
Hai Zhu220.38
Lei Yang319437.52
Xiaoqian Chen45818.29
Sofie Pollin51041113.94
Evgenii Vinogradov620.38