Dynamic visual SLAM and MEC technologies for B5G: a comprehensive review

Author:

Peng JianshengORCID,Hou Yaru,Xu Hengming,Li Taotao

Abstract

AbstractIn recent years, dynamic visual SLAM techniques have been widely used in autonomous navigation, augmented reality, and virtual reality. However, the increasing demand for computational resources by SLAM techniques limits its application on resource-constrained mobile devices. MEC technology combined with 5G ultra-dense networks enables complex computational tasks in visual SLAM systems to be offloaded to edge computing servers, thus breaking the resource constraints of terminals and meeting real-time computing requirements. This paper firstly introduces the research results in the field of visual SLAM in detail through three categories: static SLAM, dynamic SLAM, and SLAM techniques combined with deep learning. Secondly, the three major parts of the technology comparison between mobile edge computing and mobile cloud computing, 5G ultra-dense networking technology, and MEC and UDN integration technology are introduced to sort out the basic technologies related to the application of 5G ultra-dense network to offload complex computing tasks from visual SLAM systems to edge computing servers.

Funder

Innovative Research Group Project of the National Natural Science Foundation of China

The Research Project for Young and Middle-aged Teachers in Guangxi Universities

Natural Science Foundation of Guangxi Province

Special research project of Hechi University

the Innovation Fund of Chinese Universities Industry-University-Research

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

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2. Minimizing Task Age upon Decision for Low-Latency MEC Networks Task Offloading with Action-Masked Deep Reinforcement Learning;Sensors;2024-04-28

3. Research on Visual SLAM Navigation Techniques for Dynamic Environments;International Journal of Distributed Sensor Networks;2023-09-01

4. CoSAR: Multi-Robot Collaborative Semantic Mapping over Wireless Networks;2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB);2023-06-14

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