Visual-solid-state-LiDAR odometry and mapping

Yiwei Xiong; Aiying Yang; Huicheng Li; Zhao Zhou; Minqi Gao

doi:10.1117/12.2616536

8 July 2022 Visual-solid-state-LiDAR odometry and mapping

Yiwei Xiong, Aiying Yang, Huicheng Li, Zhao Zhou, Minqi Gao

Proceedings Volume 12280, 2021 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications; 1228009 (2022) https://doi.org/10.1117/12.2616536
Event: 2021 International Conference on Optical Instruments and Technology, 2022, Online Only

Abstract

Mapping through 3D lidar remains a popular technology. In the paper, we propose a method based on image to extract point cloud edge features. The image line features are mapped to the point cloud by using the camera internal and external parameter matrix obtained in advance. In addition, we propose an improved region growing method to extract the plane features in the point cloud, which has higher robustness than the method based on principal component analysis. In indoor experimental scenarios, we compare the existing methods (Li-Ho and Lili-OM) with our proposed methods. The results verified that our method can achieve a higher accuracy and frame rate.

Citation Download Citation

Yiwei Xiong, Aiying Yang, Huicheng Li, Zhao Zhou, and Minqi Gao "Visual-solid-state-LiDAR odometry and mapping", Proc. SPIE 12280, 2021 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications, 1228009 (8 July 2022); https://doi.org/10.1117/12.2616536

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