Robust place recognition for 3D range data based on point features

Abstract— The problem of place recognition appears in different mobile robot navigation problems including localization, SLAM, or change detection in dynamic environments. Whereas this problem has been studied intensively in the context of robot vision, relatively few approaches are available for threedimensional range data. In this paper, we present a novel and robust method for place recognition based on range images. Our algorithm matches a given 3D scan against a database using point features and scores potential transformations by comparing significant points in the scans. A further advantage of our approach is that the features allow for a computation of the relative transformations between scans which is relevant for registration processes. Our approach has been implemented and tested on different 3D data sets obtained outdoors. In several experiments we demonstrate the advantages of our approach also in comparison to existing techniques.

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Bastian Steder, Giorgio Grisetti, Wolfram Burgard
• Keywords: ICRA 2010, Place Recognition, Robotics, Scans, Threedimensional Range Data