Evaluation of 3D registration reliability and speed: a comparison of ICP and NDT

  • Authors:

  • Martin Magnusson;Andreas Nüchter;Christopher Lörken;Achim J. Lilienthal;Joachim Hertzberg

  • Affiliations:

  • Centre for Applied Autonomous Sensor Systems at the School of Science and Technology, University of Örebro, Örebro, Sweden;Jacobs University Bremen, Bremen, Germany and Knowledge Systems Research Group, Institute of Computer Science, University of Osnabrück, Germany;Knowledge Systems Research Group, Institute of Computer Science, University of Osnabrück, Germany;Centre for Applied Autonomous Sensor Systems at the School of Science and Technology, University of Örebro, Örebro, Sweden;Knowledge Systems Research Group, Institute of Computer Science, University of Osnabrück, Germany

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experience obtained during the original development process. This paper presents a thorough comparison of 3D scan registration algorithms based on a 3D mapping field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT). We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.