Autonomous vehicle self-localization in urban environments based on 3D curvature feature points – Monte Carlo localization
- 23 June 2021
- journal article
- research article
- Published by Cambridge University Press (CUP) in Robotica
- Vol. 40 (3), 817-833
- https://doi.org/10.1017/s0263574721000862
Abstract
This paper proposes a map-based localization system for autonomous vehicle self-localization in urban environments, which is composed of a pose graph mapping method and 3D curvature feature points – Monte Carlo Localization algorithm (3DCF-MCL). The advantage of 3DCF-MCL is that it combines the high accuracy of the 3D feature points registration and the robustness of particle filter. Experimental results show that 3DCF-MCL can provide an accurate localization for autonomous vehicles with the 3D point cloud map that generated by our mapping method. Compared with other map-based localization algorithms, it demonstrates that 3DCF-MCL outperforms them.Keywords
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