期刊文献+

基于仿生的机器人室内地图构建方法的研究 被引量:2

Research on indoor map construction method of robot based on bionic
下载PDF
导出
摘要 针对现有机器人室内地图构建算法复杂、数据量大、所需设备昂贵等问题,提出一种仿生的室内地图构建方法.该方法通过仿生人眼对颜色信息和深度信息的获取与处理,进行路径识别与路径测距.通过仿生人类对距离模糊处理的特点,运用模糊集方法进行距离判定与表示.采用二维码对环境中的标志物进行标注,形成地图定位点,通过数据库实现了地图拓扑构建与存储.实验结果表明,在复杂的室内环境中,机器人能够通过查询数据库中的地图实现在室内自主行走. In this method,the path identification and path ranging are carried out by simulating the acquiring and processing color and depth information capability of human eyes.The fuzzy set method is used to judge and express the distance by simulating the fuzzy distance expression capability of human.To simulate the experience of memorizing environment by markers,two-dimensional codes are applied to label environment markers and form positioning points.Finally,database technology is adopted to build and store the topology data of the map.The effectiveness of the method is verified in a complex indoor environment and the robot can walk autonomously by querying the constructed map database.
作者 李伟 胡雨露 黄继鹏 LI Wei;HU Yu-lu;HUANG Ji-peng(Institute of Computational Intelligence, Northeast Normal University, Changchun 130024, China)
出处 《东北师大学报(自然科学版)》 CAS CSCD 北大核心 2018年第2期84-87,共4页 Journal of Northeast Normal University(Natural Science Edition)
基金 国家自然科学基金资助项目(21227008) 吉林省科技发展计划项目(20130102028JC)
关键词 室内机器人 地图构建 机器视觉 mobile robots map-building machine vision
  • 相关文献

参考文献3

二级参考文献25

  • 1唐鸿儒,宋爱国,章小兵.基于宏行为的侦察机器人事务执行机制研究[J].机器人,2007,29(2):97-105. 被引量:8
  • 2Matthies L, Xiong Y, Hogg R, et al. A portable, au- tonomous, urban reconnaissance robot [ J ]. Robotics and Autonomous Systems, 2002, 40(2/3) : 163 -172.
  • 3Zhen J, Arjuna B, Subhash C. Autonomous vehicles navigation with visual target tracking: technical approa- chesEJ]. Algorithms, 2008, 1(2) :153 - 182.
  • 4Matthews I, Ishikawa T, Baker S. The template update problem [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(6) :810 - 815.
  • 5Miao Q, Wang G J, Shi C B, et al. A new framework for on-line object tracking based on SURF [ J]. Pattern Recognition Letters, 2011,32 ( 13 ) : 1564 - 1571.
  • 6Gai J D, Stevenson R L. Robust contour tracking based on a coupling between geodesic active contours and con- ditional random fields[ J]. Journal of Visual Communica- tion and Image Representation, 2011,22( 1 ) :33 -47.
  • 7Zhang Z X, Huang KQ, Tan T N, et al. 3D model based vehicle tracking using gradient based fimess evalu- ation under particle filter framework [ C ]//20th IEEE International Conference on Pattern Recognition. Istan- bul, Turkey, 2010:1771 - 1774.
  • 8Lowe D G. Distinctive image features from scale-invari- ant keypoints [ J ]. International Journal of Computer Vision, 2004, 60(2) :91 - 110.
  • 9Bay H, Ess A, Tuytelaars T, et al. Speeded-up robust features (SURF) [J]. Computer Vision and Image Un- derstanding, 2008, 110(3) :346 - 359.
  • 10Tuytelaars T, Schmid C. Vector quantizing feature space with a regular lattice [C]//11th IEEE Interna- tional Conference on Computer Vision. Rio de Janeiro, Brazil, 2007:670 -677.

共引文献50

同被引文献8

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部