demonstration

Edge-SLAM: edge-assisted visual simultaneous localization and mapping

Authors:

Ali J. Ben Ali,

Zakieh Sadat Hashemifar,

Karthik DantuAuthors Info & Claims

MobiCom '20: Proceedings of the 26th Annual International Conference on Mobile Computing and Networking

Article No.: 76, Pages 1 - 3

https://doi.org/10.1145/3372224.3417326

Published: 18 September 2020 Publication History

Get Access

Abstract

The recent advances in mobile devices have allowed them to run spatial sensing algorithms such as Visual Simultaneous Localization and Mapping (Visual-SLAM). However, the resource requirements of Visual-SLAM prevents long-operation of such algorithm on mobile devices. We demonstrate Edge-SLAM [2], a system that adapts edge computing into Visual-SLAM through a split architecture. Edge-SLAM offloads the compute-intensive modules of Visual-SLAM to the edge without losing accuracy. Our experiments show that Edge-SLAM architecture reduces the use of computation and memory resources on mobile devices and keeps it constant. Thus, enabling long-operation of Visual-SLAM along with other applications services on mobile devices.

References

[1]

2020. Interior Design Tv Multi-Screen - Free image on Pixabay. https://pixabay.com/images/id-828545/.

Google Scholar

[2]

Ali J. Ben Ali, Zakieh Sadat Hashemifar, and Karthik Dantu. 2020. Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services (Toronto, Ontario, Canada) (MobiSys '20). Association for Computing Machinery, New York, NY, USA, 325--337.

Digital Library

Google Scholar

[3]

Computer Vision Group in Department of Informatics at Technical University of Munich. 2020. Computer Vision Group - Dataset Download. https://vision.in.tum.de/data/datasets/rgbd-dataset/download.

Google Scholar

[4]

R. Mur-Artal and J. D. TardÃşs. 2017. ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics 33, 5 (Oct 2017), 1255--1262.

Crossref

Google Scholar

Cited By

View all

Sonkoly BNagy BDóka JKecskés-Solymosi ZCzentye JFormanek BJocha DGerő B(2024)An Edge Cloud Based Coordination Platform for Multi-user AR ApplicationsJournal of Network and Systems Management10.1007/s10922-024-09809-932:2Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10922-024-09809-9
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)Multi-user AR with EdgeSLAMEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_8(159-185)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_8
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)EdgeSLAM 2.0: Enhancing Scalability in Multi-Agent SystemsEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_4(43-77)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_4
Show More Cited By

Index Terms

Edge-SLAM: edge-assisted visual simultaneous localization and mapping

Recommendations

Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping
Localization in urban environments is becoming increasingly important and used in tools such as ARCore [18], ARKit [34] and others. One popular mechanism to achieve accurate indoor localization and a map of the space is using Visual Simultaneous ...
Edge-SLAM: edge-assisted visual simultaneous localization and mapping
MobiSys '20: Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services

Localization in urban environments is becoming increasingly important and used in tools such as ARCore [11], ARKit [27] and others. One popular mechanism to achieve accurate indoor localization as well as a map of the space is using Visual Simultaneous ...
Computation Offloading from Mobile Devices: Can Edge Devices Perform Better Than the Cloud?
ARMS-CC'16: Proceedings of the Third International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing

Mobile devices like smartphones can augment their low-power processors by offloading portions of mobile applications to cloud servers. However, offloading to cloud data centers has a high network latency. To mitigate the problem of network latency, ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

MobiCom '20: Proceedings of the 26th Annual International Conference on Mobile Computing and Networking

April 2020

621 pages

ISBN:9781450370851

DOI:10.1145/3372224

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 September 2020

Check for updates

Author Tags

Qualifiers

Demonstration

Funding Sources

National Science Foundation

Conference

MobiCom '20

Sponsor:

SIGMOBILE

MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking

September 21 - 25, 2020

London, United Kingdom

Acceptance Rates

Overall Acceptance Rate 440 of 2,972 submissions, 15%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
338
Total Downloads

Downloads (Last 12 months)15
Downloads (Last 6 weeks)4

Reflects downloads up to 12 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Sonkoly BNagy BDóka JKecskés-Solymosi ZCzentye JFormanek BJocha DGerő B(2024)An Edge Cloud Based Coordination Platform for Multi-user AR ApplicationsJournal of Network and Systems Management10.1007/s10922-024-09809-932:2Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10922-024-09809-9
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)Multi-user AR with EdgeSLAMEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_8(159-185)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_8
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)EdgeSLAM 2.0: Enhancing Scalability in Multi-Agent SystemsEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_4(43-77)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_4
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)Edge Computing in Mobile Visual SystemsEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_2(13-16)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_2
Xu JYang ZLiu YCao HXu JYang ZLiu YCao H(2024)Understanding Visual SLAMEdge Assisted Mobile Visual SLAM10.1007/978-981-97-3573-0_1(3-11)Online publication date: 6-May-2024
https://doi.org/10.1007/978-981-97-3573-0_1
Sonkoly BNagy BDÓka JKecskés-Solymosi ZCzentye JFormanek BJocha DGerő B(2023)Towards an Edge Cloud Based Coordination Platform for Multi-User AR Applications Built on Open-Source SLAMsNOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium10.1109/NOMS56928.2023.10154295(1-6)Online publication date: 8-May-2023
https://doi.org/10.1109/NOMS56928.2023.10154295
Katare DPerino DNurmi JWarnier MJanssen MDing A(2023)A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving ServicesIEEE Communications Surveys & Tutorials10.1109/COMST.2023.330247425:4(2714-2754)Online publication date: Dec-2024
https://doi.org/10.1109/COMST.2023.3302474

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping

Edge-SLAM: edge-assisted visual simultaneous localization and mapping

Computation Offloading from Mobile Devices: Can Edge Devices Perform Better Than the Cloud?