Published January 31, 2020
| Version 1.0
Journal article
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An experiment of SLAM with Quanergy M8 LiDAR sensor
Description
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.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 777720
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A comparison of registration methods for SLAM.pdf
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