摘要
同时定位与地图构建(SLAM)是当今机器人领域的主要研究课题之一。针对如何根据图像估计相机位姿问题,提出一种基于VINS的视觉里程计改进方法(ORLK-VINS)。首先,通过双目相机获取图像信息;其次,将图像信息进行直方图均衡化处理,使图像对比度和亮度得到改善;然后,对原图像特征提取算法进行改进,引入ORB算法中带有方向的FAST角点;最后再将提取的特征点进行正反向的LK光流跟踪匹配,保证匹配特征点的精确性。实验表明,经过改进后的视觉里程计相较于主流的VINS-Fusion算法,在某些场景下拥有更好的实时性和定位准确性。
Simultaneous localization and mapping(SLAM)is one of the main research topics in the field of robotics.In order to solve the problem of how to estimate the camera pose according to the image,an improved visual odomety method based on VINS(ORLK-VINS)is proposed in this paper.First of all,the image information is obtained by the stereo camera;secondly,the image information is processed by histogram equalization to improve the image contrast and brightness;then,the original image feature extraction algorithm is improved by introducing FAST corners with direction in the ORB algorithm.Finally,the extracted feature points are tracked and matched by forward and reverse LK optical flow to ensure the accuracy of the matching feature points.The experimental results show that the improved visual speedometer has better real-time performance and positioning accuracy in some scenes than the mainstream VINS-Fusion algorithm.
作者
李歆
张国良
谢波
Li Xin;Zhang Guoliang;Xie Bo(Artificial Intelligence Key Laboratory of Sichuan Province,Yibin 644000,China;School of Automation and Information Engineering,Sichuan University of Science and Engineering,Yibin 644000,China)
出处
《国外电子测量技术》
北大核心
2023年第1期20-27,共8页
Foreign Electronic Measurement Technology
基金
四川省应用基础研究项目(2019YJ00413)资助
关键词
同时定位与地图构建
视觉里程计
特征提取
跟踪匹配
simultaneous localization and mapping
visual odometry
feature extraction
tracking matching
