Robust scan matching with curvature-based matching region selection

This paper presents a novel scan matching algorithm which uses not whole scan region but only salient scan region selected around curvature-based features. A curvature function computed by the relative coordinates of neighbor scan points is used to extract salient features which are invariant to translation and rotation. Because the scan matching regions are selected around the salient features, the presented algorithm can be robustly performed even in noisy environments. The robustness of the presented algorithm was tested by datasets obtained from various noisy environments and was verified by consistently showing smaller errors than other scan matching algorithms. Moreover, the presented algorithm was successfully applied to SLAM.