Real-time RGB-D registration and mapping in texture-less environments using ranked order statistics

In this paper, we present a real time 3D SLAM system for texture-less scenes using only the depth information provided by a low cost RGB-D sensor. The proposed registration method is based on a novel informative sampling scheme that is able to extract the points carrying the most useful information from two consecutive frames. Those points are assigned 3D feature descriptors and matched with their correspondences from the other frame. A robust estimator is then used to refine the matches and estimate a rigid transformation between the frames. A global pose for the camera and associated 3D position of the points are computed by concatenating the relative transformations and a map is constructed. As a result, we are able to achieve very accurate registration in real-time using the sparse keypoints. Experimental evaluations show that our proposed method outperforms the state of the art registration algorithms in terms of accuracy and efficiency.