Study on indoor robot of self-localization based on RGB-D sensor

In order to solve the localization problem of the simultaneous localization and mapping (SLAM), a method of indoor robot´s self-localization algorithm based on RGB-D sensor was proposed. Firstly, the feature points set were extracted from the environment pictures by SURF (Speed Up Robust Features) method and the corresponding matching points were found using nearest neighbor method. Secondly, the matching points´ 3D data were reconstructed by using a combination of vision data and depth data. Thirdly, the robot´s movement parameters which are consisted of rotation matrix and transport vector are estimated by SVD and optimized by ICP algorithm. Finally, experimental results indicated the validation of the proposed method.