Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping
Abstract
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 Localization and Mapping (Visual-SLAM). However, Visual-SLAM is known to be resource-intensive in memory and processing time. Furthermore, some of the operations grow in complexity over time, making it challenging to run on mobile devices continuously. Edge computing provides additional compute and memory resources to mobile devices to allow offloading tasks without the large latencies seen when offloading to the cloud.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 29, 2022
- Source ID
- 10.1145/3561972
Entities
People
- Ali Ben Ali
- Karthik Dantu
- Marziye Kouroshli
- Sofiya Semenova
- Steven Y. Ko
- Zakieh Sadat Hashemifar
Organizations
- Air Force Research Laboratory
- Binghamton University
- National Science Foundation
- Simon Fraser University
- University at Buffalo
- Zoox