New stereo vision position and orientation measurement system for parallel robot

Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (33): 190-192.

• 工程与应用 • Previous Articles Next Articles

New stereo vision position and orientation measurement system for parallel robot

WU Di-fei¹,DING Yong-sheng^1,2,HAO Kuang-rong¹,ZHANG Shu-ping¹

1.College of Information Sciences and Technology,Donghua University,Shanghai 201620,China
2.Engineering Research Center of Digitized Textile & Fashion Technology,MOE,Donghua University,Shanghai 201620,China

Received:1900-01-01 Revised:1900-01-01 Online:2007-11-21 Published:2007-11-21
Contact: WU Di-fei

一种新型的并联机器人位姿立体视觉检测系统

吴笛飞¹,丁永生^1,2,郝矿荣¹,张淑平¹

1.东华大学信息科学与技术学院,上海 201620
2.东华大学数字化纺织服装技术教育部工程研究中心,上海 201620

通讯作者: 吴笛飞

Abstract

Abstract: This paper presents a framework of scale-invariant feature transform based stereo vision position and orientation measurement system for parallel robot.It is composed of image gather and transfer,camera calibration,Scale-Invariant Feature Transform（SIFT）,reconstruction of points and position and orientation measurement.This framework is mainly based on SIFT.It performs reliable matching between different views of objects,when the images have change in scale,rotation,shift and change in illumination.It is especially adapt to measurement for multiple DOF parallel robot and complex motions in space.In the end,position and orientation measurement for parallel robot is realized on the matlab.

Key words: SIFT, stereo vision, position and orientation measurement, 6-DOF Parallel Robot

摘要： 建立了一种并联机器人位姿立体视觉测量系统框架,主要包括图像采集与传输、摄像机标定、尺度不变量特征变换（SIFT）匹配、空间点重建和位姿测量五个部分。该系统基于SIFT,能够很好地处理图像在大视角有遮挡、平移、旋转、亮度和尺度变化时的特征点匹配,有较高的匹配精度,特别适用于对并联机器人多自由度和空间复杂运动的检测。最后使用该方法对并联机器人位姿检测做了仿真实验。

关键词: SIFT, 立体视觉, 位姿检测, 六自由度并联机器人

WU Di-fei¹,DING Yong-sheng^1,2,HAO Kuang-rong¹,ZHANG Shu-ping¹. New stereo vision position and orientation measurement system for parallel robot[J]. Computer Engineering and Applications, 2007, 43(33): 190-192.

吴笛飞¹,丁永生^1,2,郝矿荣¹,张淑平¹. 一种新型的并联机器人位姿立体视觉检测系统[J]. 计算机工程与应用, 2007, 43(33): 190-192.

[1]	XUE Mian, LIU Xiang, SHI Yunyu, XIN Binjie. Image Feature Point Extraction Algorithm to Suppress Influence of Uneven Illumination [J]. Computer Engineering and Applications, 2021, 57(4): 183-191.
[2]	WANG Junling, LU Xinming. Video Key Frame Extraction Algorithm Based on Semantic Correlation [J]. Computer Engineering and Applications, 2021, 57(4): 192-198.
[3]	HU Yaping, KONG Weiwei, LI Meng, HUANG Cuiling. Improved Panoramic Image Mosaic Algorithm for TV Image Denoising Model [J]. Computer Engineering and Applications, 2021, 57(17): 203-209.
[4]	WEI Wei, ZHANG Xinyue, ZHU Ye. Improved SIFT Algorithm Combined with Cosine Similarity for Face Matching [J]. Computer Engineering and Applications, 2020, 56(6): 207-212.
[5]	LU Peng, LU Qi, ZOU Guoliang, WANG Zhenhua, HOU Qian. Research on Time Series Image Mosaic Method Based on Improved SIFT [J]. Computer Engineering and Applications, 2020, 56(1): 196-202.
[6]	CHENG Deqiang, BAI Chunmeng, GUO Xin, LI Tengteng, ZHUANG Huandong, XU Hui. Adaptive Image Registration Algorithm Based on Hierarchical Region [J]. Computer Engineering and Applications, 2019, 55(17): 199-206.
[7]	LI Jiarui, HUANG Sicong, XU Xiuxian, KANG Xirui, WANG Pei. Multi-Source Image Matching Based on Edge Information and Extended Neighborhood [J]. Computer Engineering and Applications, 2019, 55(14): 182-190.
[8]	MU Yakun, FENG Shengwei, ZHANG Jing. Image Retrieval Based on Text and Semantic Relevance Analysis [J]. Computer Engineering and Applications, 2019, 55(1): 196-202.
[9]	XIANG Chengyu, WANG Dongli, ZHOU Yan, LI Yafang. Image classification based on RGB-D fusion feature [J]. Computer Engineering and Applications, 2018, 54(8): 178-182.
[10]	LI Heyang, SUN Yunlian, HUANG Yaxin, LI Shengmin, YU Junwei. Research on identification method of transformer bushing condition based on image matching [J]. Computer Engineering and Applications, 2018, 54(5): 211-216.
[11]	DONG Baolei1，2, LI Chaoying2, YANG Bo3, SUN Xiaobin3. Measurement of hovering accuracy of UAV based on binocular vision [J]. Computer Engineering and Applications, 2018, 54(4): 211-217.
[12]	FENG Wenbin1, LIU Baohua2. Research on image matching based on improved SIFT algorithm [J]. Computer Engineering and Applications, 2018, 54(3): 200-205.
[13]	GONG Zheng, WANG Qiang. Image matching algorithm based on microscope images [J]. Computer Engineering and Applications, 2018, 54(2): 198-202.
[14]	JIA Wenxiao1, ZHANG Guicang1, WANG Liangliang1, QIN Na2. Image registration algorithm based on SIFT and improved RANSAC [J]. Computer Engineering and Applications, 2018, 54(2): 203-207.
[15]	CAO Xiaoqian, SUN Lianshan, LI Jian. Stereo matching based on global optimization of slant-plane [J]. Computer Engineering and Applications, 2018, 54(17): 198-201.

New stereo vision position and orientation measurement system for parallel robot

一种新型的并联机器人位姿立体视觉检测系统

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics