The invention discloses an SLAM method based on fusion of a monocular vision feature method and a direct method, and the method comprises the steps of extracting DSO features from a gray level image,extracting ORB features from the DSO features, and carrying out the feature pair matching of the DSO features and the ORB features; inserting the key frame into the local map, updating the existing map points, removing redundant map points, extracting new map points from the key frame, and updating the map points; projecting the existing map points to the key frame, constructing local bundle adjustment, and adjusting the pose of the camera; removing redundant key frames, inquiring the database, carrying out Sim < 3 > similarity calculation, detecting whether a closed loop exists or not, if so,carrying out closed loop fusion, optimizing an essential diagram, and ending the process; if not, entering the next step; and constructing a global bundle adjustment, adjusting the pose of the camerato minimize the overall error of the SLAM system, and updating the map.