Int J Adv Manuf Technol (2009) 45:181–190 DOI 10.1007/s00170-009-1951-9 ORIGINAL ARTICLE Planar segmentation of data from a laser proﬁle scanner mounted on an industrial robot J. A. P. Kjellander · Mohamed Rahayem Received: 29 October 2008 / Accepted: 27 January 2009 / Published online: 24 February 2009 © Springer-Verlag London Limited 2009 Abstract In industrial applications like rapid prototyp- ing, robot vision, and geometric reverse engineering, where speed and automatic operation are important, an industrial robot and a laser proﬁle scanner can be used as a 3D measurement system. This paper is concerned with the problem of segmenting the data from such a system into regions that can be ﬁtted with planar surfaces. We have developed a new algorithm for planar segmentation based on laser scan proﬁles and robot poses. Compared to a traditional algorithm that operates on a point cloud, the new algorithm is shown to be more effective and faster. Keywords 3D measurement system · Laser proﬁle scanner · Industrial robot · Segmentation · Planar regions 1 Introduction Optical measurement systems can be used to rapidly acquire the coordinates of dense sets of 3D points from the surfaces of real world objects. One such system is the laser proﬁle scanner, see Fig. 1, which projects a straight line on the object while a digital camera cap- tures the image of the projection. Pixels representing the projected line are then joined into a 2D proﬁle. To J. A. P. Kjellander · M. Rahayem (B ) School of Science and Technology, Örebro University, SE-701 82 Örebro, Sweden e-mail: mohamed.rahayem@oru.se URL: www.oru.se/nt/cad J. A. P. Kjellander e-mail: johan.kjellander@oru.se cover the entire object the proﬁle scanner is moved along the surface and new images are captured. The result is a series of proﬁles, each captured with the scanner in a different pose. The proﬁle scanner is usu- ally mounted on a mechanical device that controls the scanner movement, or at least records the scanner pose of each proﬁle in 3D. This makes it possible to map the 2D points in the proﬁles to a common 3D coordinate system and the result is then often referred to as a point cloud. Point clouds may be used in applications like inspection, geometric reverse engineering, object recognition or navigation. In such applications the point cloud is often processed by a segmentation algorithm that uses a geometrical constraint to group points into regions representing planes, cylinders or higher order surfaces. Planar segmentation is thus deﬁned as the problem of identifying points that belong to the same plane. We believe that the industrial robot, although not widely used for this purpose, is an interesting al- ternative as a carrier of a laser proﬁle scanner. A robot is fast, ﬂexible, robust and relatively cheap compared with a coordinate measuring machine (CMM). To test the idea, we have mounted a laser proﬁle scanner on an industrial robot with a turntable, see Fig. 2 and see [17–19] for details on motion control, image processing, and noise ﬁltering. It is important to note that the absolute accuracy of an industrial robot is much lower than the accuracy of a laser proﬁle scanner. In [27], we show that the accuracy of our robot is in the range of ±400μm, while the accuracy of the laser proﬁle scanner is approx. 10 times better (±50μm). Individual proﬁles will thus be relatively accurate, but accuracy is lost when they are mapped to the point cloud. In the scope of planar segmentation, it should therefore be of interest to investigate if segmentation algorithms can