  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.
