GSR: Geometrical Scan Registration algorithm for robust and fast robot pose estimation

Abstract Undoubtedly robot localization in indoors environment where environmental information is obtained by laser range nders, which provide partial and simple information about surrounding of robots, is a challenging task. In this paper, an attempt has been made to develop an algorithm equipped with geometric pattern registration techniques to perform exact, robust, and fast robot localization purely based on laser range data. The expected pose of the robot on a precalculated map is in the form of simulated sensor readings. In order to obtain the exact pose of the robot, segmentation of both real laser range and simulated laser range readings is performed. Critical points on two scan sets are extracted from the segmented range data, and thereby the pose dierence is computed by matching similar parts of the scans and calculating the relative translation. In contrast to other self-localization
algorithms based on particle lters and scan matching, our proposed method, in common positioning scenarios, provides a linear cost with respect to the number of sensor particles, making it applicable to real-time resourcelimited embedded robots. The proposed method is able to obtain a sensibly accurate estimate of the relative pose of the robot even in non- occluded, but partially visible segments conditions. A comparison of State-ofthe-Art localization techniques has shown that GSR algorithm is superior to the other localization methods based on scan matching in accuracy, processing speed, and robustness to large positioning errors. E ectiveness of the proposed method has been demonstrated by conducting a series of simulations.