The invention discloses a sparse direct method-based monocular visual odometry (VO) method of a quadrotor unmanned-aerial-vehicle. The method is characterized by: carrying out depth estimation on a key frame, wherein feature points of the key frame are determined by a feature point method, an eigenmatrix between two adjacent frames is calculated, the eigenmatrix is decomposed and a rotation matrix and a translation matrix between the two adjacent frames are calculated to obtain an external parameter matrix, and then depths of the feature points are calculated according to a triangulation method; and after obtaining depth values of the feature points, obtaining the pose of the quadrotor unmanned-aerial-vehicle by solving through a sparse-matrix direct method, and carrying out motion estimation on all frames, wherein sparse feature points are extracted, the direct method is used to calculate a position of each feature point in the next frame, and grayscale information of each pixel point in pixel blocks which have a fixed size and are around the feature points is utilized to optimize grayscale differences between the two adjacent frames to obtain the motion pose of a camera. The method has the advantages that cumulative errors are avoided, higher accuracy is maintained for a long period, and the calculation amount can also be reduced.