—Registration is an important step when processing 3D point clouds. Applications for registration range from object modeling and tracking to simultaneous localization and mapping. This article presents the open-source Point Cloud Library (PCL) and the tools therein available for the task of point cloud registration. PCL incorporates methods for the initial alignment of point clouds using a variety of local shape feature descriptors as well as for refining initial alignments using different variants of the well-known Iterative Closest Point (ICP) algorithm. The article provides an overview on registration algorithms, usage examples of their PCL implementations, and tips for their application. Since the choice and parameterization of the right algorithm for a particular type of data is one of the biggest problems in 3D point cloud registration, we present three complete examples of data (and applications) and the respective registration pipeline in PCL. These examples include dense RG...