3D scene reconstruction system and algorithm based on stereo vision and single-line LiDAR

doi:10.13474/j.cnki.11-2246.2024.0509

Abstract

Abstract: Stereo vision and LiDAR are two effective methods for 3D scene reconstruction, but they both have some limitations. As a result, it is meaningful to fuse visual sensor data and LiDAR data in order to conquer their weaknesses. In this paper, we address the uniqueness of the single-line spinning LiDAR device, and propose a modular visual-LiDAR SLAM algorithm based on the integration of image and range data. In the method, visual information is used to undistort the LiDAR point cloud and provide an initial pose estimation from the visual odometry (VO) module. After that, pose refinement is performed by a LiDAR SLAM (L-SLAM) module which is independent from the VO module, and then we obtain highly accurate 3D scene reconstruction results. Experiments show that our system and algorithm could increase the accuracy and adaptation of low-cost large-scale 3D scene reconstruction tasks.

Key words: stereo vision, LiDAR, 3D reconstruction

CLC Number:

P237

ZHONG Leisheng, XIA Hui, CHEN Jialin. 3D scene reconstruction system and algorithm based on stereo vision and single-line LiDAR[J]. Bulletin of Surveying and Mapping, 2024, 0(5): 48-52,59.

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