The invention belongs to the technical field of computer vision, image processing and three-dimensional measurement, and particularly relates to a 3D-RGB point cloud registration method based on a local gray scale sequence model descriptor. The method comprises the following steps: 1, calculating a four-neighborhood gray average value of each point in two point clouds; 2, dividing adjacent pointsof the key points into six parts according to gray values, and finally connecting the feature vectors of the six parts in series to form a key point feature descriptor; 3, constructing a point-to-point mutual corresponding relationship between the source point cloud and the target point cloud according to a nearest neighbor ratio method and an Euclidean distance threshold, and removing an error corresponding relationship by utilizing random sampling consistency and color consistency; and 4, solving a conversion matrix between the source point cloud and the target point cloud by using the corresponding relationship, and performing spatial transformation on the source point cloud to complete registration of the point cloud. According to the method, the influence of unobvious geometric information and light intensity change on point cloud registration can be effectively reduced. The method has a wider application range. The precision and the robustness of three-dimensional point cloud registration are improved.