A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks

August 24, 2019 ยท The Cartographer ยท ๐Ÿ› Journal of Global Positioning Systems

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks"

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Authors Baichuan Huang, Jun Zhao, Jingbin Liu arXiv ID 1909.05214 Category cs.RO: Robotics Citations 118 Venue Journal of Global Positioning Systems Last Checked 1 day ago
Abstract
Simultaneous Localization and Mapping (SLAM) achieves the purpose of simultaneous positioning and map construction based on self-perception. The paper makes an overview in SLAM including Lidar SLAM, visual SLAM, and their fusion. For Lidar or visual SLAM, the survey illustrates the basic type and product of sensors, open source system in sort and history, deep learning embedded, the challenge and future. Additionally, visual inertial odometry is supplemented. For Lidar and visual fused SLAM, the paper highlights the multi-sensors calibration, the fusion in hardware, data, task layer. The open question and forward thinking with an envision in 6G wireless networks end the paper. The contributions of this paper can be summarized as follows: the paper provides a high quality and full-scale overview in SLAM. It's very friendly for new researchers to hold the development of SLAM and learn it very obviously. Also, the paper can be considered as a dictionary for experienced researchers to search and find new interesting orientation.
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