CELLO-3D: Estimating the Covariance of ICP in the Real World

@article{Landry2018CELLO3DET,
  title={CELLO-3D: Estimating the Covariance of ICP in the Real World},
  author={David Landry and François Pomerleau and Philippe Gigu{\`e}re},
  journal={2019 International Conference on Robotics and Automation (ICRA)},
  year={2018},
  pages={8190-8196}
}
The fusion of Iterative Closest Point (ICP) registrations in existing state estimation frameworks relies on an accurate estimation of their uncertainty. In this paper, we study the estimation of this uncertainty in the form of a covariance. First, we scrutinize the limitations of existing closed-form covariance estimation algorithms over 3D datasets. Then, we set out to estimate the covariance of ICP registrations through a data-driven approach, with over 5100000 registrations on 1020 pairs… CONTINUE READING

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