Visual simultaneous localization and mapping（SLAM） technology has become one of the important navigation methods in the field of navigation and positioning. In order to improve the comprehensive performance of visual SLAM in all-weather and multi-scene environments， the visual SLAM technology integrating various information has been developed rapidly. This paper systematically reviews the research results of visual SLAM in recent years. First， the key links of front-end odometry， back-end optimization， loop closure detection and map construction in visual and visual/inertial SLAM are summarized. Second， in the analysis of pure visual SLAM technology， the two main types of visual SLAM methods based on traditional geometric transformation and modern deep learning are discussed， and related representative visual SLAM technologies are sorted out. Third， based on the detailed description of the multi-information fusion SLAM method of visual/inertial combined navigation， the progress of SLAM navigation technology based on heterogeneous image vision and its combination with inertial sensor in recent years is analyzed. Finally， the future development direction of visual SLAM is prospected.