An Edge Cloud Based Coordination Platform for Multi-user AR Applications

被引:1
作者
Sonkoly, Balazs [1 ,3 ,4 ]
Nagy, Balint Gyorgy [1 ,3 ,4 ]
Doka, Janos [1 ,3 ,4 ]
Kecskes-Solymosi, Zsofia [1 ,3 ]
Czentye, Janos [1 ,3 ,4 ]
Formanek, Bence [2 ]
Jocha, David [2 ]
Gero, Balazs Peter [2 ]
机构
[1] Budapest Univ Technol & Econ, Fac Elect Engn & Informat, Dept Telecommun & Media Informat, HSN Lab, Budapest, Hungary
[2] Ericsson Res, Budapest, Hungary
[3] MTA BME Network Softwarizat Res Grp, Budapest, Hungary
[4] HUN REN BME Cloud Applicat Res Grp, Budapest, Hungary
关键词
Augmented reality; Edge computing; SLAM; COLLABORATIVE AUGMENTED REALITY; MONOCULAR VISUAL SLAM; SIMULTANEOUS LOCALIZATION; TECHNOLOGIES; ARCHITECTURE; CHALLENGES; TRENDS;
D O I
10.1007/s10922-024-09809-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Augmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However, multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate position and orientation information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure. Our solution is built on open-source SLAM libraries and the Robot Operating System (ROS). Our contribution is threefold. First, we propose an extensible, edge cloud based AR architecture. Second, we develop a proof-of-concept prototype supporting multiple devices and building on an AI-based SLAM selection component. Third, a dedicated measurement methodology is described, including energy consumption aspects as well, and the overall performance of the system is evaluated via real experiments.
引用
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页数:24
相关论文
共 77 条
[1]  
Ait-Jellal R, 2017, 2017 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR)
[2]  
Al-Hiyari N.N., 2021, International Conference on Data Science, E-learning and Information Systems 2021, P107, DOI DOI 10.1145/3460620.3460741
[3]  
Ali A.J.B., 2020, MOBICOM 20 26 ANN IN, DOI [10.1145/3372224.3417326, DOI 10.1145/3372224.3417326]
[4]  
Alriksson F., 2021, Ericsson Technol. Rev., V2021, P2
[5]  
Amazon, 2024, Digital twins made easy-AWS IoT TwinMaker-Amazon Web Services
[6]  
ARCore, about us
[7]  
ARkit, about us
[8]  
Benavidez P, 2015, ANN IEEE SYST CONF, P773, DOI 10.1109/SYSCON.2015.7116844
[9]   Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving [J].
Bresson, Guillaume ;
Alsayed, Zayed ;
Yu, Li ;
Glaser, Sebastien .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2017, 2 (03) :194-220
[10]   The EuRoC micro aerial vehicle datasets [J].
Burri, Michael ;
Nikolic, Janosch ;
Gohl, Pascal ;
Schneider, Thomas ;
Rehder, Joern ;
Omari, Sammy ;
Achtelik, Markus W. ;
Siegwart, Roland .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2016, 35 (10) :1157-1163