The invention discloses a structured scene vision SLAM (Simultaneous Localization and Mapping) method based on point-line-surface features, which comprises the following steps of: firstly, inputting a color image and a corresponding depth image, extracting the point-line-surface features in the image and carrying out feature matching; then detecting a Manhattan world coordinate system according to a plane normal vector, if the Manhattan world coordinate system exists and appears in a Manhattan world map, calculating a camera attitude and tracking point-line-plane feature estimation displacement, otherwise, tracking the point-line-plane feature estimation pose; performing key frame judgment on the current frame, and if the current frame is a key frame, inserting the key frame into a local map; maintaining map information and performing joint optimization on the current key frame, the adjacent key frames and the three-dimensional features; and finally, loopback detection is carried out, and if a closed-loop frame is detected, loopback is closed and global optimization is carried out. The method is a visual SLAM method with high precision and strong robustness, and solves the problem that the visual SLAM precision is reduced and even the system is invalid only based on point features in a low-texture structured scene.