Edge Computing in 5G for Drone Navigation: What to Offload?

被引：39

作者：

Hayat, Samira ^{[1
]}

Jung, Roland ^{[2
]}

Hellwagner, Hermann ^{[1
,2
]}

Bettstetter, Christian ^{[2
,3
]}

Emini, Driton ^{[4
]}

Schnieders, Dominik ^{[4
]}

机构：

[1] Univ Klagenfurt, Inst Informat Technol ITEC, A-9020 Klagenfurt, Austria

[2] Univ Klagenfurt, Karl Popper Kolleg Networked & Aerial Vehicles NA, A-9020 Klagenfurt, Austria

[3] Univ Klagenfurt, Inst Networked & Embedded Syst NES, A-9020 Klagenfurt, Austria

[4] Deutsch Telekom AG, Bonn, Germany

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2021年 / 6卷 / 02期

关键词：

Aerial systems; autonomous vehicle navigation; perception and autonomy; vision-based navigation;

D O I：

10.1109/LRA.2021.3062319

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Small drones that navigate using cameras may be limited in their speed and agility by low onboard computing power. We evaluate the role of edge computing in 5G for such autonomous navigation. The offloading of image processing tasks to an edge server is studied with a vision-based navigation algorithm. Three computation modes are compared: onboard, fully offloaded to the edge, and partially offloaded. Partial offloading is expected to pose lower demands on the communication network in terms of transfer rate than full offloading but requires some onboard processing. Our results on the computation time help select the most suitable mode for image processing, i.e., whether and what to offload, based on the network conditions.

引用

页码：2571 / 2578

页数：8

共 20 条

[1] Energy-Efficient Computation Offloading for Secure UAV-Edge-Computing Systems [J].