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Certification.md

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Certification

  • CorAl – Are the point clouds Correctly Aligned?

    Adolfsson, Daniel, et al. "CorAl–Are the point clouds Correctly Aligned?." 2021 European Conference on Mobile Robots (ECMR). IEEE, 2021.

    Citations: 1

    [pdf]

    • Summary
      • Differential entropy for separate point cloud and joint cloud(Which in fact the sum of covariance of the points).
      • Only overlapping points are used in the computation(The definition of overlapping points).

  • Efficient Continuous-Time SLAM for 3D Lidar-Based Online Mapping

    Droeschel, David, and Sven Behnke. "Efficient continuous-time SLAM for 3D lidar-based online mapping." 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018.

    Citations: 108

    [pdf]

    • Summary

  • Entropy Minimization SLAM Using Stereo Vision

    Sáez, Juan Manuel, and Francisco Escolano. "Entropy minimization SLAM using stereo vision." Proceedings of the 2005 IEEE International Conference on Robotics and Automation. IEEE, 2005.

    **Citations:**44

    • It also provides a kind of way based on information theory to measure the quality of point set alignment. It only gives a value, not a certification.

  • Learning-based Localizability Estimation for Robust LiDAR ✔️

    Nubert, Julian, et al. "Learning-based Localizability Estimation for Robust LiDAR Localization." arXiv preprint arXiv:2203.05698 (2022).

    [pdf]

    • Summary
      • The work is based on deep learning. The proposed method is used to estimate whether a point cloud can be registered well.
        • The training data is generated manually, specifically, the input data first sampled and use ICP to register to get a result. So the inputs are point cloud and an estimated registration error.
        • Then after training, the network can predict whether a point cloud can be registered well or not.