Robust Localization with Low-Mounted Multiple LiDARs in Urban Environments
IEEE International Conference on Intelligent Transportation (ITSC) 2019
In this paper, we propose a robust, real-time and scalable localization framework for multi-LiDAR equipped vehicles in challenging urban environments. Our test vehicle uses multiple LiDARs with low mounting positions which makes the localization task very challenging in dense traffic scenarios due to the reduced field-of-view of LiDARs and additional uncertainty introduced by the dynamic vehicles. In order to increase the robustness and provide consistently smooth localization output, LiDAR localization is fused with the dead reckoning using the probabilistic scan matching confidence estimation method. We conducted experiments in different urban settings and results confirmed that our framework can operate reliably with low-position multi-LiDAR suite under various traffic scenarios.