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On the Covariance of ICP-based Scan-matching Techniques

Abstract : This paper considers the problem of estimating the covariance of roto-translations computed by the Iterative Closest Point (ICP) algorithm. The problem is relevant for localization of mobile robots and vehicles equipped with depth-sensing cameras (e.g., Kinect) or Lidar (e.g., Velodyne). The closed-form formulas for covariance proposed in previous literature generally build upon the fact that the solution to ICP is obtained by minimizing a linear least-squares problem. In this paper, we show this approach needs caution because the rematching step of the algorithm is not explicitly accounted for, and applying it to the point-to-point version of ICP leads to completely erroneous covariances. We then provide a formal mathematical proof why the approach is valid in the point-to-plane version of ICP, which validates the intuition and experimental results of practitioners.
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Contributor : François Goulette <>
Submitted on : Tuesday, May 9, 2017 - 4:32:13 PM
Last modification on : Wednesday, October 14, 2020 - 3:52:36 AM


  • HAL Id : hal-01519995, version 1


Silvère Bonnabel, Martin Barczyk, François Goulette. On the Covariance of ICP-based Scan-matching Techniques. 2016 American Control Conference (ACC), Jul 2016, Boston, United States. ⟨hal-01519995⟩



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