The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 535–540, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-535-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 535–540, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-535-2020

  06 Aug 2020

06 Aug 2020

SEGMENT-BASED LIDAR ODOMETRY FOR LESS STRUCTURED OUTDOOR SCENE

W. Wu, C. Chen, J. Li, Y. Cong, and B. Yang W. Wu et al.
  • State Key Laboratory of Information Engineering in Survey, Mapping and Remote Sensing, Wuhan University, No. 129, Luoyu Road, Wuhan, P.R. China

Keywords: LiDAR Odometry, Point Cloud Segmentation, LiDAR SLAM, Mobile Mapping System, Unmanned Ground Vehicle

Abstract. Accurate registration of sparse sequential point clouds data frames acquired by a 3D light detection and ranging (LiDAR) sensor like VLP-16 is a prerequisite for the back-end optimization of general LiDAR SLAM algorithms to achieve a globally consistent map. This process is also called LiDAR odometry. Aiming to achieve lower drift and robust LiDAR odometry in less structured outdoor scene using a low-cost wheeled robot-borne laser scanning system, a segment-based sampling strategy for LiDAR odometry is proposed in this paper. Proposed method was tested in two typical less structured outdoor scenes and compared with other two state of the art methods. The results reveal that the proposed method achieves lower drift and significantly outperform the state of the art.