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NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation.

, , , , , , and . ICRA, page 5654-5660. IEEE, (2021)

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Incorporating ego-motion uncertainty estimates in range data registration., , , , and . IROS, page 1389-1395. IEEE, (2017)An evaluation of CFEAR Radar Odometry., and . CoRR, (2024)TBV Radar SLAM - trust but verify loop candidates., , , , and . CoRR, (2023)Towards introspective loop closure in 4D radar SLAM., , , , and . CoRR, (2024)NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation., , , , , , and . ICRA, page 5654-5660. IEEE, (2021)Lidar-Level Localization With Radar? The CFEAR Approach to Accurate, Fast, and Robust Large-Scale Radar Odometry in Diverse Environments., , , , and . IEEE Trans. Robotics, 39 (2): 1476-1495 (April 2023)CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry., , , , and . IROS, page 5462-5469. IEEE, (2021)A Submap per Perspective - Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality., , , , and . ECMR, page 1-7. IEEE, (2019)CorAl - Are the point clouds Correctly Aligned?, , , , and . ECMR, page 1-7. IEEE, (2021)Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments., , , , , and . ICRA, page 4386-4392. IEEE, (2020)