The ability of unmanned platforms to achieve autonomous positioning and navigation in a wide range of environments is increasingly demanding, in which Lidar-based Simultaneous Localization and Mapping (SLAM) is the mainstream of research schemes. In this work, this paper systematically outlines the framework and key modules of 3D Lidar SLAM algorithm, analyses and describes recent research hotspot problems and future development trends, collates the evaluation criteria for the performance of 3D Lidar SLAM algorithm, based on these, selects six representative mature open source 3D Lidar SLAM algorithms, which are then tested and evaluated on the robot operating system (ROS), based on the KITTI benchmark data set, the parallel comparison is carried out from three aspects: KITTI official precision standard, SLAM algorithm precision index, algorithm time consuming and processing frame rate. The results show that the LIO-SAM algorithm has the best performance among the six algorithms. The RMSE data of ATE and RPE in the 00 sequence data set test are 1. 303 and 0. 028, respectively, and the processing frame rate of the algorithm is 28. 6. Finally, the application trend of 3D laser SLAM technology is discussed based on CiteSpace analysis.