For the traditional pose estimation method based on point pair features, both the preprocessing of scene point cloud and the construction of point pair features of scene point cloud have serious time-consuming problems, which cannot meet the needs of actual industry. Therefore, this paper proposes a pose estimation method that combines instance segmentation and point pair features. Therefore, this paper proposes a pose estimation method that combines instance segmentation and point pair features. First, use the Mask R-CNN-based instance segmentation network to obtain the location of the target object in the two-dimensional image of the scene; then, obtain the local point cloud data of the space where the target object is located from this position and the depth information of the scene; finally, the local the point cloud data is used as the scene point cloud based on point pair feature pose estimation to perform feature matching with the point cloud of the target object.