= PDF Reprint, = BibTeX entry, = Online Abstract
W. S. Grant, R. C. Voorhies, L. Itti, Finding Planes in LiDAR Point Clouds for Real-Time Registration, In: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4347-4354, Nov 2013. [2013 acceptance rate: 43%] (Cited by 46)
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.
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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