测绘通报 ›› 2024, Vol. 0 ›› Issue (5): 48-52,59.doi: 10.13474/j.cnki.11-2246.2024.0509

• 学术研究 • 上一篇    

基于双目视觉和单线激光雷达的三维场景重建系统和算法

钟雷声, 夏辉, 陈佳林   

  1. 92728部队, 上海 200436
  • 收稿日期:2023-08-11 发布日期:2024-06-12
  • 作者简介:钟雷声(1991—),男,博士,研究方向为计算机视觉与三维重建。E-mail:zx007zls@foxmail.com

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

ZHONG Leisheng, XIA Hui, CHEN Jialin   

  1. Troops 92728, Shanghai 200436, China
  • Received:2023-08-11 Published:2024-06-12

摘要: 双目视觉和激光雷达是实现三维场景重建的两种有效方法,但它们都具有自身的局限性。将视觉传感器和激光传感器的数据相融合,可克服其各自的缺陷,具有重要意义。本文针对单线旋转激光雷达设备的独特性,提出了一种基于双目图像和激光雷达数据的模块化双目视觉-激光雷达SLAM(Stereo-LiDAR SLAM)系统和算法。在该方法中,双目视觉信息被用于消除激光雷达点云的畸变,并支撑双目视觉定位(VO)模块,为整个系统提供初始的位姿估计。然后,独立于VO模块的激光雷达SLAM(L-SLAM)模块对位姿参数进行优化,从而得到高精度的三维场景重建结果。试验表明,本文设计的系统和算法可以有效提高大规模低成本三维场景重建的精度和环境适应能力。

关键词: 双目视觉, 激光雷达, 三维重建

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

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