A_Survey_of_SLAM
The source file of paper and frame in Visio and XMind (A Survey of Simultaneous Localization and Mapping)
1.A Survey of Simultaneous Localization and Mapping
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 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 dictionary for experienced researchers to search and find new interested orientation.
2.Paper
v1,24 Aug 2019
v2,12 Oct 2019
v3,01 Jan 2020
3.Frame
The Frame in Visio (Mostly in Chinese) and in Xmind (Chinese) are supplied, which are correspond with v1 currently. You can use it as a reference quickly and easily.
4.Cite
@article{Huang2019ASO,
title={A Survey of Simultaneous Localization and Mapping},
author={Baichuan Huang and Jun Zhao and Jingbin Liu},
journal={ArXiv},
year={2019},
volume={abs/1909.05214}
}