基于改进ORB特征的单目视觉SLAM算法  

MONOCULAR VISUAL SLAM ALGORITHM BASED ON IMPROVED ORB FEATURE

作　　者：程珉 陈临强[1] 杨全鑫 Cheng Min;Chen Linqiang;Yang Quanxin(School of Computer,Hangzhou Dianzi University,Hangzhou 310018,Zhejiang,China)

机构地区：[1]杭州电子科技大学计算机学院,浙江杭州310018

出　　处：《计算机应用与软件》2021年第10期242-248,266,共8页Computer Applications and Software

基　　金：国家自然科学基金项目(61672009)。

摘　　要：单目视觉SLAM算法容易受场景纹理影响出现初始化失败或者相机轨迹漂移的问题。为此,提出一种基于改进ORB特征的单目视觉SLAM算法。对输入视频帧构建高斯金字塔提取FAST特征,综合考虑特征点的灰度信息与其邻域的梯度信息生成描述子,并采用多网格策略划分特征点邻域,凭借改进的特征点降低运动模型算法的迭代次数,达到较好的时间效率。实验表明,该算法的相机轨迹精度与特征匹配精度相较于ORB-SLAM得到有效提高,并且能很好地适应多种纹理特殊场景。Monocular visual SLAM algorithm is easily affected by scene texture,which leads to initialization failure,and camera trajectory drift.Aiming at the above problems,the monocular visual SLAM algorithm based on improved ORB features is proposed.Firstly,a Gaussian pyramid was constructed to extract FAST features for the input video frame.Then the gray information of the feature point and the gradient information of its neighborhood were comprehensively considered to generate descriptors,and the multi-grid strategy was used to divide the image patch.Finally,with the improved feature points,the number of iterations of the model algorithm was reduced,so that the time efficiency was better.The experiments show that the camera track accuracy and feature point accuracy of improved ORB-SLAM are increased compared with ORB-SLAM,and it can adapt well to multiple weak texture scenes.

关 键 词：视觉SLAM 特征匹配 ORB 场景纹理 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]