Finding Planes in LiDAR Point Clouds for Real-Time Registration. Grant, W‥, Voorhies, R‥, & Itti, L. In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nov, 2013.
abstract   bibtex   
We present a robust plane finding algorithm that when combined with plane-based frame-to-frame registration gives accurate real-time pose estimation. Our plane extraction is capable of handling large and sparse datasets such as those generated from spinning multi-laser sensors such as the Velodyne HDL-32E LiDAR. We test our algorithm on frame-to-frame registration in a closed-loop indoor path comprising 827 successive 3D laser scans (over 57 million points), using no additional information (e.g., odometry, IMU). Our algorithm outperforms, in both accuracy and time, three state-of-the-art methods, based on iterative closest point (ICP), plane-based randomized Hough transform, and planar region growing.
@inproceedings{ Grant_etal13iros,
  author = {W.S. Grant and R.C. Voorhies and L. Itti},
  title = {Finding Planes in LiDAR Point Clouds for Real-Time Registration},
  abstract = {We present a robust plane finding algorithm that when combined with
          plane-based frame-to-frame registration gives accurate real-time
          pose estimation.  Our plane extraction is capable of handling large
          and sparse datasets such as those generated from spinning multi-laser sensors such as the Velodyne HDL-32E
          LiDAR.  We test our algorithm on frame-to-frame registration
          in a closed-loop indoor path comprising 827 successive 3D laser
          scans (over 57 million points), using no additional information
          (e.g., odometry, IMU). Our algorithm outperforms, in both accuracy
          and time, three state-of-the-art methods, based on iterative closest
          point (ICP), plane-based randomized Hough transform, and planar
          region growing.},
  booktitle = {Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = {2013},
  month = {Nov},
  review = {full/conf},
  type = {bb},
  if = {2013 acceptance rate: 43%}
}

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