Line Segmentation Of 2d Laser Scanner Point Clouds For Indoor Slam Based On A Range Of Residuals

M. Peter, S. R. U. N. Jafri, G. Vosselman

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

11 Citations (Scopus)


Indoor mobile laser scanning (IMLS) based on the Simultaneous Localization and Mapping (SLAM) principle proves to be the preferred method to acquire data of indoor environments at a large scale. In previous work, we proposed a backpack IMLS system containing three 2D laser scanners and an according SLAM approach. The feature-based SLAM approach solves all six degrees of freedom simultaneously and builds on the association of lines to planes. Because of the iterative character of the SLAM process, the quality and reliability of the segmentation of linear segments in the scanlines plays a crucial role in the quality of the derived poses and consequently the point clouds. The orientations of the lines resulting from the segmentation can be influenced negatively by narrow objects which are nearly coplanar with walls (like e.g. doors) which will cause the line to be tilted if those objects are not detected as separate segments. State-of-the-art methods from the robotics domain like Iterative End Point Fit and Line Tracking were found to not handle such situations well. Thus, we describe a novel segmentation method based on the comparison of a range of residuals to a range of thresholds. For the definition of the thresholds we employ the fact that the expected value for the average of residuals of n points with respect to the line is σ / √n. Our method, as shown by the experiments and the comparison to other methods, is able to deliver more accurate results than the two approaches it was tested against.
Original languageEnglish
Title of host publicationProceedings ISPRS Geospatial Week 2017, 18-22 September 2017, Wuhan, China
EditorsD. Li
PublisherInternational Society for Photogrammetry and Remote Sensing (ISPRS)
Number of pages7
Publication statusPublished - 2017
EventISPRS Geospatial Week 2017 - Wuhan, China
Duration: 18 Sept 201722 Sept 2017 (Full text Open Access proceedings)

Publication series

NameISPRS Annals
VolumeVolume IV-2/W4


ConferenceISPRS Geospatial Week 2017
Internet address


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