• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 图形与图像 • 上一篇    下一篇

基于Kinect传感器和ORB特征的视觉SLAM算法设计与实现

许芬,王振   

  1. (北方工业大学电气与控制工程学院,北京 100144)
  • 收稿日期:2016-08-18 修回日期:2016-12-23 出版日期:2018-05-25 发布日期:2018-05-25

Design & implementation of a visual SLAM algorithm
based on Kinect sensor and ORB feature

XU Fen,WANG Zhen   

  1. (School of Electrical & Control Engineering,North China University of Technology,Beijing 100144,China)
  • Received:2016-08-18 Revised:2016-12-23 Online:2018-05-25 Published:2018-05-25

摘要:

介绍了一个基于嵌入式平台和Kinect传感器的同时定位与地图创建算法的设计与实现。Kinect传感器包括一个可见光彩色摄像头和一个利用结构光测量深度的红外CMOS摄像头。 算法利用ORB算子作为环境特征点的描述信息,并利用基于边沿的最近邻修复方法对深度图像进行修正以获得完整的深度信息。在此基础上,利用LSH方法进行特征点的匹配。实验结果表明,基于ORB特征的视觉SLAM算法具有较好的实用性和良好的定位精度,可以广泛应用于室内机器人的自主导航任务。

关键词: 嵌入式视觉, 视觉SLAM, ORB特征, 移动机器人

Abstract:

This paper designs and implements a visual Simultaneous Localization And Mapping (SLAM) algorithm based on embedded platform and Kinect sensors. Kinect sensors consist of a RGB camera and an infrared CMOS camera that uses structured light to measure depth. The algorithm uses the Oriented FAST and Rotated BRIEF (ORB) operator as the description information of the environmental feature points and uses the nearest neighbor repairing method based on edge detection to correct the depth image so as to obtain a complete depth map. Based on this, Locality-Sensitive Hashing (LSH) algorithm is used to match feature points. Experimental results show that the visual SLAM algorithm based on ORB features is feasible, has good positioning accuracy, and can be widely used in autonomous navigation tasks of indoor robots.
 

Key words: embedded vision, visual SLAM, ORB feature, mobile robot