留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于双目立体视觉的目标空间坐标计算及姿态估计

黄青丹 何彬彬 宋浩永 饶锐 赵宝玉 王国库

黄青丹, 何彬彬, 宋浩永, 饶锐, 赵宝玉, 王国库. 基于双目立体视觉的目标空间坐标计算及姿态估计[J]. 华南师范大学学报(自然科学版), 2020, 52(2): 9-13. doi: 10.6054/j.jscnun.2020020
引用本文: 黄青丹, 何彬彬, 宋浩永, 饶锐, 赵宝玉, 王国库. 基于双目立体视觉的目标空间坐标计算及姿态估计[J]. 华南师范大学学报(自然科学版), 2020, 52(2): 9-13. doi: 10.6054/j.jscnun.2020020
HUANG Qingdan, HE Binbin, SONG Haoyong, RAO Rui, ZHAO Baoyu, WANG Guoku. Space Coordinate Calculation and Attitude Estimation Based on Binocular Stereo Vision[J]. Journal of South China normal University (Natural Science Edition), 2020, 52(2): 9-13. doi: 10.6054/j.jscnun.2020020
Citation: HUANG Qingdan, HE Binbin, SONG Haoyong, RAO Rui, ZHAO Baoyu, WANG Guoku. Space Coordinate Calculation and Attitude Estimation Based on Binocular Stereo Vision[J]. Journal of South China normal University (Natural Science Edition), 2020, 52(2): 9-13. doi: 10.6054/j.jscnun.2020020

基于双目立体视觉的目标空间坐标计算及姿态估计

doi: 10.6054/j.jscnun.2020020
基金项目: 

南方电网公司科技项目 GZHKJXM20160055

详细信息
    通讯作者:

    黄青丹,教授级高级工程师,Email:18829588@qq.com

  • 中图分类号: TP242.6

Space Coordinate Calculation and Attitude Estimation Based on Binocular Stereo Vision

  • 摘要: 基于双目立体视觉的目标空间坐标计算及姿态估计方法、双目立体视觉系统标定和双目视觉系统校准技术,构建了三维场景中目标的空间坐标与图像中点像素坐标的对应方法.通过双目立体视觉系统采集目标图像,采用基于半全局立体匹配(SGBM)方法,实现了目标中心点三维坐标的计算,并通过背景差分的手段获得目标轮廓,获取目标在水平面的旋转角度,配合焦点所处的坐标位置标示,即可提取目标姿态信息.采用以上方法对电力仪表的姿态进行估计和验证,结果表明:设计的方法可以完成电力仪表的空间坐标计算以及姿态估计,可实现对电力仪表的准确抓取,为机器人在电力系统人工智能领域的应用提供参考.
  • 图  1  双目立体视觉模型

    Figure  1.  The binocular stereo vision model

    图  2  标定使用的左相机图像

    Figure  2.  The left camera images used for calibration

    图  3  立体匹配效果

    Figure  3.  The stereo matching effect

    图  4  背景差分法提取仪表轮廓的流程图

    Figure  4.  The flow chart of instrument outline extraction with the background difference method

    图  5  仪表轮廓的提取结果

    Figure  5.  The results of instrument outline extraction

    图  6  电力仪表抓取系统的实物图

    Figure  6.  The physical map of power meter grab system

    图  7  不同距离下三维坐标Z的误差

    Figure  7.  The errors in Z of three-dimensional coordinates at different distances

    表  1  匹配结果及误差

    Table  1.   The matching results and errors  mm

    序号 三维坐标 匹配坐标 误差
    1 [27.16,2.57,511.72] [28.23,2.89,510.88] [-1.07,-0.32,0.84]
    2 [4.15,-1.32,509.78] [4.21,0.11,508.16] [-0.06,-1.43,-1.24]
    3 [-43.14,-14.93,510.22] [-42.07,-10.28,508.76] [-1.07,-4.65,-1.46]
    4 [-38.76,-12.47,509.84] [-36.47,-7.19,509.13] [-2.29,-5.28,0.71]
    5 [-40.76,-17.23,509.87] [-38.45,-16.01,509.52] [-2.31,-1.22,-0.35]
    6 [96.21,-16.32,509.75] [92.17,-14.91,509.58] [4.04,-1.41,0.17]
    7 [35.87,8.49,510.72] [34.68,9.51,509.89] [1.19,-1.02,-0.83]
    8 [-47.09,-18.93,509.94] [-44.25,-16.80,509.32] [-2.84,-2.13,-0.62]
    9 [-37.91,-13.67,511.84] [-36.34,-10.13,511.68] [-1.43,-2.57,-1.72]
    10 [31.45,-0.27,509.67] [28.69,2.15,509.92] [2.76,1.88,-0.25]
    下载: 导出CSV

    表  2  本文方法与SIFT特征匹配方法对比

    Table  2.   the comparison of the proposed method and the SIFT method

    匹配方法 平均坐标绝对误差/mm 平均计算时间/s
    本文方法 6.156 8.101
    SIFT特征匹配方法 8.412 8.056
    下载: 导出CSV
  • [1] SOVOBODA T, KYBIC J, HLAVAC V. Image processing, analysis & and machine vision-a MATLAB companion[M]. New York:Thomson Learning, 2008.
    [2] PENG J, XU W, HAN Y. An efficient pose measurement method of a space non-cooperative target based on stereo vision[J]. IEEE Access, 2017, 5:22344-22362. doi: 10.1109/ACCESS.2017.2759798
    [3] 贾丙西, 刘山, 张凯祥, 等.机器人视觉伺服研究进展:视觉系统与控制策略[J].自动化学报, 2015, 41(5):861-873. http://d.old.wanfangdata.com.cn/Periodical/jqr200403019

    JIA B X, LIU S, ZHANG K X, et al. Survey on robot visual servo control:vision system and control strategies[J]. Acta Automatica Sinica, 2015, 41(5):861-873. http://d.old.wanfangdata.com.cn/Periodical/jqr200403019
    [4] 周芳.双目视觉中立体匹配算法的研究与实现[D].大连: 大连理工大学, 2013.

    ZHOU F. Research on stereo matching in binocular vision and its implementation[D]. Dalian: Dalian University of Technology, 2013.
    [5] PENG J, XU W, LIANG B, et al. Pose measurement and motion estimation of space non-cooperative targets based on laser radar and stereo-vision fusion[J]. IEEE Sensors Journal, 2019, 19(8):3008-3019. doi: 10.1109/JSEN.2018.2889469
    [6] ZHANG Q, WANG Y, WANG L. Registration of images with affine geometric distortion based on maximally stable extremal regions and phase congruency[J]. Image & Vision Computing, 2015, 36:23-39. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=0876fd97b03e1e3f1a3523afe8b5400d
    [7] 蔡晓妍, 戴冠中, 杨黎斌.一种快速的单模式匹配算法[J].计算机应用研究, 2008, 25(1):45-46;81. doi: 10.3969/j.issn.1001-3695.2008.01.011

    CAI X Y, DAI G Z, YANG L B. Faster algorithm for single pattern matching[J]. Application Research of Computers, 2008, 25(1):45-46;81. doi: 10.3969/j.issn.1001-3695.2008.01.011
    [8] GOLDBERG S B, MAIMONE M W, MATTHIES L. Stereo vision and rover navigation software for planetary exploration[C]//2002 IEEE Aerospace Conference Proceedings. Montana: IEEE, 2002.
    [9] TSAI R Y. A versatile camera calibration technique for high-accuracy 3d machine vision metrology using off-the-shelf TV cameras and lenses[J]. IEEE Journal of Robotics and Automation, 1987, 3(4):323-344. doi: 10.1109/JRA.1987.1087109
    [10] ZHANG Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11):1330-1334. doi: 10.1109/34.888718
    [11] 李小文.利用拉普拉斯-高斯模板进行边缘检测[J].华南师范大学学报(自然科学版), 1997(2):53-55. http://journal-n.scnu.edu.cn/article/id/1686

    LI X W. Edge detection using Laplacian-of-Gaussian masks[J]. Journal of South China Normal University (Natural Science Edition), 1997(2):53-55. http://journal-n.scnu.edu.cn/article/id/1686
    [12] 倪爱伟.基于双目立体视觉的三维定位技术研究[D].南京: 南京航空航天大学, 2009.

    NI A W. Study on three dimension reconstruction technique based on stereo vision[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009.
    [13] 李胜利.基于双目立体视觉的工件识别与定位技术研究[D].哈尔滨: 哈尔滨工业大学, 2016.

    LI S L. Research on workpiece recognition and location technology based on binocular stereo vision[D]. Harbin: Harbin Institute of Technology, 2016.
    [14] OKADA K, INABA M, INOUE H. Integration of real-time binocular stereo vision and whole body information for dynamic walking navigation of humanoid robot[C]//Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI2003. Piscataway: IEEE, 2003.
    [15] 何佳唯.基于双目视觉的机器人定位技术研究[D].无锡: 江南大学, 2016.

    HE J W. Research of robot positioning technology[D]. Wuxi: Jiangnan University, 2016.
    [16] ZENG Z, YAN H. Region matching and optimal matching pair theorem[C]//International Conference on Computer Graphics. Piscataway: IEEE, 2001.
  • 加载中
图(7) / 表(2)
计量
  • 文章访问数:  3803
  • HTML全文浏览量:  1267
  • PDF下载量:  69
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-08-29
  • 刊出日期:  2020-04-25

目录

    /

    返回文章
    返回