An efficient corner detection and matching algorithm for 2D lidar data

The feature detection of LIDAR data and their matching are essential for the localization and map-making of a mobile vehicle. In this study, an efficient detection algorithm for the corner points in a LIDAR data is proposed using line segments or corner points as general features. The proposed algorithm detects the corner points using the relationship between the adjacent measurement points. A virtual line segment consisting of two corner points detected in a data set is used by the matching algorithm in this study to compute the transformation including the translation and the orientation between two measurement data sets. Because the length of a line segment in a data set is preserved by the transformation, finding a corresponding line segment with similar length in the other measurement data set is easy. Experimental results verify the performance of the corner detection and the matching algorithm proposed in this study.