Using Augmented Measurements to Improve the Convergence of ICP

  • Jacopo Serafin
  • Giorgio Grisetti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8810)

Abstract

Point cloud registration is an essential part for many robotics applications and this problem is usually addressed using some of the existing variants of the Iterative Closest Point (ICP) algorithm. In this paper we propose a novel variant of the ICP objective function which is minimized while searching for the registration. We show how this new function, which relies not only on the point distance, but also on the difference between surface normals or surface tangents, improves the registration process. Experiments are performed on synthetic data and real standard benchmark datasets, showing that our approach outperforms other state of the art techniques in terms of convergence speed and robustness.

Keywords

Point Cloud Registration ICP Surface Normals 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jacopo Serafin
    • 1
  • Giorgio Grisetti
    • 1
  1. 1.Dept. of Computer, Control and Management EngineeringSapienza University of RomeRomeItaly

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