空间站机械臂位姿测量中合作靶标的快速识别

doi:10.7527/S1000-6893.2014.0118

材料工程与机械制造

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空间站机械臂位姿测量中合作靶标的快速识别

温卓漫^1,2, 王延杰^1,1, 初广丽^1,2,3, 金明河⁴

1. 中国科学院长春光学精密机械与物理研究所, 长春 130033;
2. 中国科学院大学, 北京 100049;
3. 白城师范学院, 白城 137000;
4. 哈尔滨工业大学机器人技术与系统国家重点实验室, 哈尔滨 150080

收稿日期:2014-05-06 修回日期:2014-06-10 出版日期:2015-04-15 发布日期:2014-06-18
通讯作者: 王延杰Tel.: 0431-86176560 E-mail: wangyj@ciomp.ac.cn E-mail:wangyj@ciomp.ac.cn
作者简介:温卓漫女, 博士研究生。主要研究方向: 数字图像处理,机器视觉。E-mail: wenzhuoman@gmail.com;王延杰男, 研究员, 博士生导师。主要研究方向: 数字图像处理,电视跟踪和自动目标识别技术。Tel: 0431-86176560 E-mail: wangyj@ciomp.ac.cn
基金资助:
国家"973"计划 (2013CB733103)

Fast recognition of cooperative target used for position and orientation measurement of space station's robot arm

WEN Zhuoman^1,2, WANG Yanjie^1,1, CHU Guangli^1,2,3, JIN Minghe⁴

1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
2. The University of the Chinese Academy of Sciences, Beijing 100049, China;
3. Baicheng Normal University, Baicheng 137000, China;
4. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China

Received:2014-05-06 Revised:2014-06-10 Online:2015-04-15 Published:2014-06-18
Supported by:
National Basic Research Program of China(2013CB733103)

摘要/Abstract

摘要：

空间站机械臂在完成辅助对接或者目标抓捕时,需要实时求取机械臂上的视觉传感器与目标上的合作靶标之间的位置和姿态,而其前提条件是合作靶标的快速识别。本文提出了一种合作靶标的快速识别算法。算法分为3大步骤:首先用Sobel算子和改进的非极大值抑制算法提取靶标图像的单像素边缘;然后将每条边缘分为两段,分别采用最小二乘法进行圆拟合,若两段拟合结果相似则该边缘属于圆形;最后根据圆形的大小在每个圆形周围开出一大一小两个正方形窗口,统计在两窗的补集内距离圆心较近的直线数量,若直线数量满足规定条件则认为是合作靶标。利用手眼相机、六自由度转台和合作靶标对算法进行了验证,实验结果表明该算法能在1.5 m的距离内准确识别合作靶标,且不受光照条件影响。合作靶标的识别算法快速、稳定、抗干扰能力强。

关键词: 机器视觉, 目标识别, 非极大值抑制, 圆检测, 直线检测

Abstract:

When space station's robot arm performs auxiliary docking or target arresting, position and orientation between the visual sensor fixed on robot arm and the cooperative target on object must be measured in real-time, and its prerequisite is fast recognition of cooperative target. A fast recognition algorithm of cooperative target is proposed. The algorithm consists of three steps. To begin with, Sobel operator and the improved non-maximum suppression algorithm are hired to extract single pixel edges in the picture of cooperative target. Moreover, every edge is split into two sections, and each section is fitted into a circle using least square circle fitting method. If two halves have similar fitting results, the edge belongs to a circle. Finally, we draw two square windows around each circle according to the circle's radius, one big and one small. The number of straight lines that are in the complement area of the two windows and are close to the circle center is counted, and the cooperative target is identified if the number of straight lines suites the predetermined condition. Experiments using hand-eye camera, six-DOF turntable and the cooperative target are executed to test our algorithm. Results demonstrate that the proposed algorithm can accurately identify the cooperative target within a distance of 1.5 m regardless of lighting condition. In conclusion, the cooperative target recognition method is fast and stable and has strong anti-interference capability.

Key words: robot vision, target identification, non-maximum suppression, circle detection, line detection

中图分类号:

V526
TP391.4

温卓漫, 王延杰, 初广丽, 金明河. 空间站机械臂位姿测量中合作靶标的快速识别[J]. 航空学报, 2015, 36(4): 1330-1338.

WEN Zhuoman, WANG Yanjie, CHU Guangli, JIN Minghe. Fast recognition of cooperative target used for position and orientation measurement of space station's robot arm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(4): 1330-1338.

参考文献

[1] Wei C, Zhao Y, Tian H. Grasping control of space robot for capturing floating target [J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(3): 633-637 (in Chinese). 魏承, 赵阳, 田浩. 空间机器人捕获漂浮目标的抓取控制[J]. 航空学报, 2010, 31(3): 633-637.
[2] Cong P C, Sun Z W. Research of impact issues during dual-arm space manipulator capturing object[J]. Journal of Sichuan University: Engineering Science Edition, 2010, 42(4): 235-241 (in Chinese). 丛佩超, 孙兆伟. 双臂式空间机械臂捕捉目标的碰撞问题研究[J]. 四川大学学报: 工程科学版, 2010, 42(4): 235-241.
[3] Zhang F H, Fu Y L, Wang S G. Adaptive control of free-floating space robot with inertia parameter uncertainties [J]. Acta Aeronautica et Astronautica Sinica, 2012, 32(12): 2347-2354 (in Chinese). 张福海, 付宜利, 王树国. 惯性参数不确定的自由漂浮空间机器人自适应控制研究[J]. 航空学报, 2012, 32(12): 2347-2354.
[4] Liang J, Chen L. Improved nonlinear feedback control for free-floating space-based robot with time-delay based on predictive and approximation of Taylor series[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(1): 163-169 (in Chinese). 梁捷, 陈力. 具有时延的漂浮基空间机器人基于泰勒级数预测、逼近的改进非线性反馈控制[J]. 航空学报, 2012, 33(1): 163-169.
[5] Li J, Yuan F, Hu Y H. Attitude measurement of space objects based on multi-linear CCD and multi-point cooperation target[J]. Optics and Precision Engineering, 2013, 21(6): 1635-1641 (in Chinese). 李晶, 袁峰, 胡英辉. 基于多点合作目标的多线阵CCD空间物体姿态测量[J]. 光学精密工程, 2013, 21(6): 1635-1641.
[6] Wei X Q, Huang J M, Chen F, et al. Research on super close distance independent image navigation of cooperative target[J]. Manned Spaceflight, 2012, 18(2): 28-39 (in Chinese). 魏祥泉, 黄建明, 陈凤, 等. 合作目标超近距离自主影像导航技术研究[J]. 载人航天, 2012, 18(2): 28-39.
[7] Liang B, Du X D, Li C, et al. Advances in space robot on-orbit servicing for non-cooperative spacecraft[J]. Robot, 2012, 34(2): 243-256 (in Chinese). 梁斌, 杜晓东, 李成, 等. 空间机器人非合作航天器在轨服务研究进展[J]. 机器人, 2012, 34(2): 243-256.
[8] Wen Z M, Wang Y J, Di N, et al. On-orbit hand-eye calibration using cooperative target[J]. Chinese Journal of Scientific Instrument, 2014, 35(5): 1005-1012 (in Chinese). 温卓漫, 王延杰, 邸男, 等. 基于合作靶标的在轨手眼标定[J]. 仪器仪表学报, 2014, 35(5): 1005-1012.
[9] Zhou F, Yang C, Wang C G, et al. Circle detection and its number identification in complex condition based on random Hough transform[J]. Chinese Journal of Scientific Instrument, 2013, 34(3): 623-627 (in Chinese). 周封, 杨超, 王晨光, 等. 基于随机Hough变换的复杂条件下圆检测与数目辨识 [J]. 仪器仪表学报, 2013, 34(3): 623-627.
[10] Duan L M, Wang W, Zhang X. Circle detection through improved Hough transform[J]. Computer Integrated Manufacturing Systems, 2013, 19(9): 2148-2152 (in Chinese). 段黎明, 汪威, 张霞. 改进的Hough变换实现圆检测[J]. 计算机集成制造系统, 2013, 19(9): 2148-2152.
[11] Liu Y J, Lai R F, Rong W B, et al. A fast center detecting method based on improved randomized Hough trans-form[J]. Nanotechnology and Precision Engineering, 2011, 9(4): 298-304 (in Chinese). 刘延杰, 赖日飞, 荣伟彬, 等. 基于改进随机Hough 变换的快速中心检测方法[J]. 纳米技术与精密工程, 2011, 9(4): 298-304.
[12] Wu J P, Li J X, Xiao C S, et al. Real-time robust algorithm for circle object detection [C]//The 9th International Conference for Young Computer Scientists, 2008: 1722-1727.
[13] Pratt W K. Digital image processing[M]. Deng L H, Zhang Y H, translated. Beijing: China Machine Press, 2005: 330-331 (in Chinese). Pratt W K. 数字图像处理[M]. 邓鲁华, 张延恒, 译. 北京: 机械工业出版社, 2005: 330-331.
[14] Wang J, Wang H L, Xiang M S, et al. Sub-pixel accuracy central location of circle target based on non-maximum suppression[J]. Chinese Journal of Scientific Instrument, 2012, 33(7): 1460-1468 (in Chinese). 王静, 王海亮, 向茂生, 等. 基于非极大值抑制的圆目标亚像素中心定位 [J]. 仪器仪表学报, 2012, 33(7): 1460-1468.
[15] He F Y, Tian Z, Liu X Z, et al. A fast edge tracking algorithm for image segmentation using a simple Markov random field model[C]//International Conference on Computer Science and Electronics Engineering, 2012: 633-636.
[16] Tri C P, Yong S I, Ja C K, et al. An enhanced edge tracking method using a low resolution tactile sensor[J]. International Journal of Control, Automation, and Systems, 2010, 8(2):462-467.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

空间站机械臂位姿测量中合作靶标的快速识别

Fast recognition of cooperative target used for position and orientation measurement of space station's robot arm

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