Abstract
LiDAR based SLAM is becoming affordable by new sensors such as the M8 Quanergy LiDAR, but there is still little work reporting on the accuracy attained with them. In this paper we report on the comparison of three registration methods applied to the estimation of the path followed by the LiDAR sensor and the registration of the overall cloud of points, namely the iterated closest points (ICP), Coherent Point Drift (CPD), and Normal Distributions Transform (NDT) registration methods. In our experiment, we found that the NDT method provides the most robust performance.
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Acknowledgments
This work has been partially supported by FEDER funds through MINECO project TIN2017-85827-P, and grant IT1284-19 as university research group of excellence from the Basque Government.
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Aguilar-Moreno, M., GraƱa, M. (2021). A Comparison of Registration Methods for SLAM with the M8 Quanergy LiDAR. In: Herrero, Ć., Cambra, C., Urda, D., Sedano, J., QuintiĆ”n, H., Corchado, E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020. Advances in Intelligent Systems and Computing, vol 1268. Springer, Cham. https://doi.org/10.1007/978-3-030-57802-2_79
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DOI: https://doi.org/10.1007/978-3-030-57802-2_79
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