基于改进M-ORB的视觉SLAM直接-闭环检测算法

李伟; 任孟瀚; 黄威豪; 杜晓玉; 周毅

doi:10.11959/j.issn.2096-6652.202148

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基于改进M-ORB的视觉SLAM直接-闭环检测算法

学术论文 | 更新时间：2024-06-05

- 基于改进M-ORB的视觉SLAM直接-闭环检测算法
- Improved M-ORB based direct-loop closure detection algorithm for visual SLAM
- 智能科学与技术学报 2021年3卷第4期页码：482-491
- 作者机构：
  
  1. 河南大学计算机与信息工程学院，河南开封475004
  2. 河南省车联网协同技术国际联合实验室，河南开封 475004
  3. 鹰驾科技（深圳）有限公司，广东深圳518052
- 作者简介：
  
  [ "李伟（1979- ），女，河南大学计算机与信息工程学院副教授，主要研究方向为机器人导航、运动规划和控制" ]
  [ "任孟瀚（1997- ），男，河南大学计算机与信息工程学院硕士生，主要研究方向为机器人导航控制、路径规划" ]
  [ "黄威豪（1996- ），男，河南大学计算机与信息工程学院硕士生，主要研究方向为机器人导航控制、图像处理" ]
  [ "杜晓玉（1979- ），女，博士，河南大学计算机与信息工程学院副教授，主要研究方向为无线传感器网络定位及覆盖技术" ]
  [ "周毅（1981- ），男，博士，河南大学计算机与信息工程学院教授、博士生导师，河南省车联网协同技术国际联合实验室主任，主要研究方向为机器人导航控制、车联网技术" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61701170);河南省科技发展计划项目;The Program for Science and Technology Development of Henan Province(202102210327);河南省科技发展计划项目;The Program for Science and Technology Development of Henan Province(202102310198);河南省科技发展计划项目;The Program for Science and Technology Development of Henan Province(202102210412)
- DOI：10.11959/j.issn.2096-6652.202148
  中图分类号： TP242
- 网络出版日期：2021-12，
  
  纸质出版日期：2021-12-15
- 稿件说明：
移动端阅览
李伟, 任孟瀚, 黄威豪, 等. 基于改进M-ORB的视觉SLAM直接-闭环检测算法[J]. 智能科学与技术学报, 2021,3(4):482-491.

Wei LI, Menghan REN, Weihao HUANG, et al. Improved M-ORB based direct-loop closure detection algorithm for visual SLAM[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 482-491.
李伟, 任孟瀚, 黄威豪, 等. 基于改进M-ORB的视觉SLAM直接-闭环检测算法[J]. 智能科学与技术学报, 2021,3(4):482-491. DOI： 10.11959/j.issn.2096-6652.202148.

Wei LI, Menghan REN, Weihao HUANG, et al. Improved M-ORB based direct-loop closure detection algorithm for visual SLAM[J]. Chinese journal of intelligent science and technology, 2021, 3(4): 482-491. DOI： 10.11959/j.issn.2096-6652.202148.

摘要

直接法SLAM不在前端提取图像特征点，使得后端无法生成视觉词袋，这导致大部分直接法SLAM无法使用带有词袋模型的闭环检测来消除系统的累积误差。针对此问题，提出一种基于改进M-ORB的视觉SLAM直接-闭环检测算法，生成闭环检测所需的词袋模型，然后采用词频-逆文档频率算法对视觉词典树各个子节点中的视觉单词进行自适应分配权重，得到场景信息的准确表述。在TUM、KITTI两种公开数据集上进行了对比实验，实验结果表明，所提出的算法能够有效检测到闭环，并在不降低准确性的同时，提高SLAM的实时性与鲁棒性。

Abstract

Most kinds of direct methods do not extract image feature points in the front end of SLAM system

resulting in that they cannot use loop closure detection with bag-of-words models to eliminate the cumulative error of the system.To resolve this problem

an improved mature-oriented fast and rotated BRIEF (M-ORB) based direct-loop closure detection algorithm for visual SLAM was proposed

which designed an improved M-ORB

generated the bag of words model required for loop closure detection

and then used the term frequency-inverse document frequency (TF-IDF) algorithm to adaptively assign weights to the visual words in each sub-node of the dictionary tree.Finally

an accurate representation of the scene information was obtained.In the end

the proposed algorithm and conducted comparative experiments were verified though two public data sets TUM and KITTI.The experimental results show that the algorithm proposed in this paper can effectively detect the loop closure

and has better real-time and robustness performance without reducing the accuracy.

关键词

Keywords

references

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