基于双目强约束的直接稀疏视觉里程计

叶培楚; 李东; 章云

doi:10.12052/gdutxb.200138

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基于双目强约束的直接稀疏视觉里程计

更新时间：2026-05-27

- 基于双目强约束的直接稀疏视觉里程计
- Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints
- 广东工业大学学报 2021年38卷第4期页码：65-70
- 作者机构：
  
  广东工业大学自动化学院,广东,广州,510006
- 作者简介：
  
  叶培楚(1996–)，男，硕士研究生，主要研究方向为视觉SLAM、特征匹配、人脸识别
  李东(1983–)，男，副教授，博士，硕士生导师，主要研究方向为模式识别、机器学习、人脸识别和机器视觉，E-mail：dong.li@gdut.edu.cn
- 基金信息：
  
  广东省自然科学基金资助项目(2021A1515011867)
- DOI：10.12052/gdutxb.200138
  中图分类号： TP391.4
- 网络首发：2021-07-10，
  
  纸质出版：2021
- 稿件说明：
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叶培楚, 李东, 章云. 基于双目强约束的直接稀疏视觉里程计[J]. 广东工业大学学报, 2021, 38(4): 65-70.

Ye Pei-chu, Li Dong, Zhang Yun. Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints[J]. 2021, 38(4): 65-70.
叶培楚, 李东, 章云. 基于双目强约束的直接稀疏视觉里程计[J]. 广东工业大学学报, 2021, 38(4): 65-70. DOI： 10.12052/gdutxb.200138.

Ye Pei-chu, Li Dong, Zhang Yun. Direct Sparse Visual Odometer Based on Enhanced Stereo-Camera Constraints[J]. 2021, 38(4): 65-70. DOI： 10.12052/gdutxb.200138.

摘要

为了提高双目直接稀疏里程计(Stereo Direct Sparse Odometry

Stereo DSO)的定位速度和精度

使得移动机器人可以更有效地执行任务

提出了一种基于双目强约束的直接稀疏视觉里程计系统。基于直接法的即时定位与地图构建(Simultaneous Localization and Mapping

SLAM)系统直接对图像像素构建光度误差优化函数

无需提取特征点

克服了基于特征点法的SLAM系统在弱纹理场景下不鲁棒的缺陷

并且在前端跟踪阶段效率更高。提出一种快速、准确的双目初始化方法

结合三角化不确定性为不同类型的点赋予不同的深度范围

加速深度滤波器的收敛。同时

在运动估计阶段引入双目约束

使得该系统在绝对尺度上的定位更加准确。通过在公开的KITTI数据集11个序列上进行实验

实验结果表明所提出的算法在定位精度上明显优于同样采用直接法的Stereo Large Scale Direct SLAM(LSD-SLAM2)和Stereo DSO

并达到与基于特征点法的ORB-SLAM3相近的水平

为直接法SLAM提供一种更优的定位方案。

Abstract

A new direct SLAM (Simultaneous Localization And Mapping) system with enhanced stereo-camera constrains based on Stereo Direct Sparse Odometry (Stereo DSO) is presented. As a direct SLAM method

any image pixel with sufficient intensity gradient can be utilized

which makes it robust even in featureless areas. Two-stage checking combining SAD (Sum of Absolute Differences) with NCC (Normalized Cross Correlation) matching method is used for stereo matching and triangulated uncertainty concerned to accelerate the convergence of depth filters. To estimate the accurate scale of the environment

static stereo constrains are added to the tracking module. Our evaluation on KITTI demonstrates that the proposed system achieves the better performance than the state of the art direct SLAM systems such as LSD-SLAM2 and Stereo DSO

and achieves the comparable performance with ORB-SLAM3 which is the state of the art feature SLAM. The proposal provides mobile robots with a new direct SLAM system to explore the environment more precisely and robustly.

关键词

Keywords

references

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