Segmentation based lidar odometry and mapping

Yinan Wang; Rongchuan Cao; Tianqi Zhang; Kun Yan; Xiaoli Zhang

doi:10.1117/12.2644264

12 October 2022 Segmentation based lidar odometry and mapping

Yinan Wang, Rongchuan Cao, Tianqi Zhang, Kun Yan, Xiaoli Zhang

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123422L (2022) https://doi.org/10.1117/12.2644264
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

LiDAR based Simultaneous Localization and Mapping (LiDAR SLAM) plays a vital role in autonomous driving and has attracted the attention of researchers. In order to achieve higher accuracy of motion estimation between adjacent LiDAR frames and reconstruction of the map, a segmentation-based LiDAR odometry and mapping framework is proposed in this paper. In detail, we first define the classification of several features with weak semantic information, the extraction method of which is achieved by a segmentation algorithm proposed in this paper that is based on greedy search. Based on the above work, a novel point cloud registration algorithm is also proposed in this paper, which is solved by modeling the problem as a nonlinear optimization problem. In order to verify the effectiveness of the proposed model, we collect a large amount of data in the autonomous driving test area to test it and compare the results with the existing state-of-the-art models. The experimental results show that the algorithm proposed in this paper can run stably in real-world autonomous driving scenarios and has smaller error and higher robustness compared with other models.

Citation Download Citation

Yinan Wang, Rongchuan Cao, Tianqi Zhang, Kun Yan, and Xiaoli Zhang "Segmentation based lidar odometry and mapping", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123422L (12 October 2022); https://doi.org/10.1117/12.2644264

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KEYWORDS

Clouds

LIDAR

Data modeling

Feature extraction

Error analysis

Unmanned vehicles

Associative arrays

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