双目立体视觉技术在潜孔钻机钻孔定位中的应用

吴万荣, 史建, 徐智

江苏大学学报(自然科学版) ›› 2015, Vol. 36 ›› Issue (1) : 65-69.

PDF(1609 KB)
全国中文核心期刊
中国科技核心期刊
RCCES核心期刊
SCD核心期刊
PDF(1609 KB)
江苏大学学报(自然科学版) ›› 2015, Vol. 36 ›› Issue (1) : 65-69. DOI: 10.3969/j.issn.1671-7775.2015.01.012
论文

双目立体视觉技术在潜孔钻机钻孔定位中的应用

作者信息 +

Application of binocular stereo vision in downthehole drill position

Author information +
文章历史 +

摘要

为了提高潜孔钻机定位的精度,提出采用双目立体视觉技术获得潜孔钻机定位过程中孔位标识的三维位置信息,用于指导潜孔钻机进行自动钻孔定位.首先利用双目摄像机获取含有孔位标识的图像对,然后采用隶属度函数为梯形函数的模糊阈值分割方法对孔位标识进行识别分割,利用图像的不变矩原理求取孔位标识的质心,并通过三角测量原理求取孔位的空间位置信息.最后,在潜孔钻机试验台上进行了基于双目立体视觉系统的自动定位试验.结果表明,所采用以灰度直方图为基础的模糊阈值分割能够实现对孔位标识有效信息的提取,且定位误差小于25 mm.

Abstract

In order to improve accuracy of downthehole (DTH) drill position, binocular stereo vision was adopted to obtain a 3D location measurement of holes marker for DTH position. A pair of stereo images with holes marker were obtained by stereo cameras to be segmented by fuzzy thresholding method based on trapezoidal membership functions. The holes marker centroid was extracted by image invariant moment principle. The holes marker 3D locations were obtained by triangulation principle. On DTH testbed, the autonomous position experiments were implemented based on binocular stereo vision system. The experiment results show that the holes marker can be efficiently segmented by fuzzy thresholding method based on trapezoidal membership functions with position error less than 25 mm.

关键词

潜孔钻机 / 双目立体视觉 / 模糊阈值分割 / 质心提取 / 三维位置信息

Key words

DTH drill / binocular stereo vision / fuzzy threshold segmentation / centroid extraction / 3D locations

引用本文

导出引用
吴万荣, 史建, 徐智. 双目立体视觉技术在潜孔钻机钻孔定位中的应用[J]. 江苏大学学报(自然科学版), 2015, 36(1): 65-69 https://doi.org/10.3969/j.issn.1671-7775.2015.01.012
WU Wan-Rong, SHI Jian, XU Zhi. Application of binocular stereo vision in downthehole drill position[J]. Journal of Jiangsu University(Natural Science Edition), 2015, 36(1): 65-69 https://doi.org/10.3969/j.issn.1671-7775.2015.01.012

参考文献

[1]Ramstrm M. Atlas Copco drill rigs for mine automation and communicationa totally new technology platform for advanced mining systems [J]. CIM Magazine, 2005,98:1088.
[2]Xiong Qingshan, Li Jia, Liu Shuangliang, et al. The computerized simulation software development of the pneumatic DTH[J]. Advanced Materials Research, 2011, doi: 104028/www.scientific.net/AMR.317-3192113.
[3]Vrde P, Westin J, Sangireddy S, et al. Rig control system: WIPO patent 2012173563 [P]. 2012-12-21.
[4]陈志. 一种新型旋挖钻机回转定位系统的设计[J]. 筑路机械与施工机械化, 2013(1):76-77,81.
Chen Zhi. Design of new type of rotary positioning system for rotary drilling rig [J]. Road Machinery & Construction Mechanization, 2013(1): 76-77,81. (in Chinese)
[5]顾勇,何明昕.基于机器视觉的啤酒瓶检测系统研究[J].计算机工程与设计, 2012,33(1):248-253.
Gu Yong, He Mingxin. Research on beer bottle detection system based on machine vision [J]. Computer Engineering and Design, 2012,33(1): 248-253. (in Chinese)
[6]孙俊,芦兵,毛罕平.基于双目识别技术的复杂背景中果实识别试验[J].江苏大学学报:自然科学版, 2011, 32(4): 423-427.
Sun Jun, Lu Bing, Mao Hanping. Fruits recognition in complex background using binocular stereovision[J]. Journal of Jiangsu University: Natural Science Edition, 2011, 32(4): 423-427. (in Chinese)
[7]Cuevas E, Zaldivar D, PérezCisneros M. A novel multithreshold segmentation approach based on differential evolution optimization[J]. Expert Systems with Applications, 2010, 37(7): 5265-5271.
[8]Lopes N V, Mogadouro do Couto P A, Bustince H, et al. Automatic histogram threshold using fuzzy measures[J]. IEEE Transactions on Image Processing, 2010, 19(1): 199-204.
[9]蔡健荣,周小军,王锋,等.柑橘采摘机器人障碍物识别技术[J].农业机械学报,2009,40 (11):171-175.
Cai Jianrong, Zhou Xiaojun, Wang Feng, et al. Obstacle identification of citrus harvesting robot [J]. Transactions of the Chinese Society for Agricultural Machinery, 2009, 40(11):171-175. (in Chinese)
[10]Liu Dong, Jiang Zhaohui, Feng Huanqing. A novel fuzzy classification entropy approach to image thresholding[J]. Pattern Recognition Letters, 2006, 27(16): 1968-1975.

基金

国家自然科学基金资助项目(51175518)


PDF(1609 KB)

99

Accesses

0

Citation

Detail

段落导航
相关文章

/