Abstract
A 3D LIDAR simultaneous localization and map** scheme with intensity information corrected point clouds is proposed for the traditional simultaneous localization and map** (slam) methods. Four modules are included in the algorithm: data processing, feature extraction, odometry and map**. The improved scheme is tested and analysed against the currently popular LOAM and LEGO-LOAM schemes using real measurement data. The results show that the proposed method changes the existing pre-processing method without any increase in pre-processing time. The test results show that the optimization algorithm outperforms the LOAM scheme while meeting the system’s real-time requirements, but is inferior the LEGO-LOAM scheme.
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Acknowledgments
This work was supported in part by the Tian** Artificial Intelligence Project of China (No. 18ZXAQSF00090), the Tian** University Discipline Leading Talent Training Program of China (No. SSW181030105), and the Tian** Artificial Intelligence Project of China (No. 2020YJSZXS3 2).