• DocumentCode
    3521862
  • Title

    An analytical least-squares solution to the line scan LIDAR-camera extrinsic calibration problem

  • Author

    Guo, Chuangxin ; Roumeliotis, Stergios I.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA
  • fYear
    2013
  • fDate
    6-10 May 2013
  • Firstpage
    2943
  • Lastpage
    2948
  • Abstract
    In this paper, we present an elegant solution to the 2D LIDAR-camera extrinsic calibration problem. Specifically, we develop a simple method for establishing correspondences between a line-scan (2D) LIDAR and a camera using a small calibration target that only contains a straight line. Moreover, we formulate the nonlinear least-squares problem for finding the unknown 6 degree-of-freedom (dof) transformation between the two sensors, and solve it analytically to determine its global minimum. Additionally, we examine the conditions under which the unknown transformation becomes unobservable, which can be used for avoiding ill-conditioned configurations. Finally, we present extensive simulation and experimental results for assessing the performance of the proposed algorithm as compared to alternative analytical approaches.
  • Keywords
    calibration; cameras; least squares approximations; optical radar; robots; sensor fusion; 2D LIDAR-camera extrinsic calibration problem; analytical least-squares solution; calibration target; line scan LIDAR-camera extrinsic calibration problem; line-scan 2D LIDAR; nonlinear least-squares problem; sensors; Calibration; Cameras; Laser radar; Noise; Noise measurement; Polynomials; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2013 IEEE International Conference on
  • Conference_Location
    Karlsruhe
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-4673-5641-1
  • Type

    conf

  • DOI
    10.1109/ICRA.2013.6630985
  • Filename
    6630985