Research seminar "Image-based Techniques for Efficient Processing 3D Point Clouds"

Abstract:

In robotics the field of environment sensing advanced by sensors yielding 3D points clouds. 3D information available in real-time enables autonomous robots to navigate in unknown environments, e.g., in the field of inspection and rescue robotics. Important application areas include industrial automation, architecture, agriculture, and the construction or maintenance of tunnels and mines. This talk presents challenges and recent results on using classical images-based methods on 3D point cloud data. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere can be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, and many other projection methods and the use of state-of-the-art feature detectors and descriptors to solve relibaly the registration and SLAM problem. Furthermore, we apply image compression methods to the generated panorama images. Challenges arise from the high-dynamic range of modern sensors. The talk presents the results of several lossless compression methods and the lossy JPEG on point cloud compression. While lossless compression methods are designed to retain the original data, there is a need for post-processing algorithms in case of lossy compression.

CV:

Andreas Nüchter is professor of computer science (telematics) at University of Würzburg, Germany. Before summer 2013 he headed as assistant professor the Automation group at Jacobs University Bremen. Prior he was a research associate at University of Osnabrück. Further past affiliations were with the Fraunhofer Institute for Autonomous Intelligent Systems (AIS, Sankt Augustin), the University of Bonn, from which he received the diploma degree in computer science in 2002 (best paper award by the German society of informatics (GI) for his thesis) and the Washington State University. He holds a doctorate degree (Dr. rer. nat) from University of Bonn. His thesis was shortlisted for the EURON PhD award. Andreas works on robotics and automation, cognitive systems and artificial intelligence. His main research interests include reliable robot control, 3D environment mapping, 3D vision, and laser scanning technologies. The capabilities of his 3D robotic SLAM approaches were demonstrated at RoboCup Rescue competitions, ELROB and several other events. He is a member of the GI and the IEEE.