Analysis of position estimation precision by cooperative target with three feature points

ZHAO Lian-jun; LIU En-hai; ZHANG Wen-ming; ZHAO Ru-jin

doi:10.3788/OPE.20142205.1190

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Analysis of position estimation precision by cooperative target with three feature points

更新时间：2020-08-13

- Analysis of position estimation precision by cooperative target with three feature points
- Optics and Precision Engineering Vol. 22, Issue 5, Pages: 1190-1197(2014)
- 作者机构：
  
  1. 中国科学院大学北京,中国,100049
  2. 中国科学院光电技术研究所,四川成都,610209
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20142205.1190
  CLC： TP242
- Received：18 August 2013，
  
  Revised：20 September 2013，
  
  Published：25 May 2014
- 稿件说明：
移动端阅览
赵连军, 刘恩海, 张文明等. 单目三点位置测量精度分析[J]. 光学精密工程, 2014,22(5): 1190-1197

ZHAO Lian-jun, LIU En-hai, ZHANG Wen-ming etc. Analysis of position estimation precision by cooperative target with three feature points[J]. Editorial Office of Optics and Precision Engineering, 2014,22(5): 1190-1197
赵连军, 刘恩海, 张文明等. 单目三点位置测量精度分析[J]. 光学精密工程, 2014,22(5): 1190-1197 DOI： 10.3788/OPE.20142205.1190.

ZHAO Lian-jun, LIU En-hai, ZHANG Wen-ming etc. Analysis of position estimation precision by cooperative target with three feature points[J]. Editorial Office of Optics and Precision Engineering, 2014,22(5): 1190-1197 DOI： 10.3788/OPE.20142205.1190.

摘要

通过理论推导，对影响三点单目视觉位置姿态测量系统的6个因素（标志器与相机的相对距离，标志器尺寸，相机量化误差，相机内参数标定误差，特征点的中心提取精度，姿态解算算法精度）以及这些因素对系统精度的影响程度进行了分析，然后通过数值仿真和成像试验验证了理论推导的正确性。实验结果表明，对测量精度影响最大的因素是测量距离，像平面方向的测量误差与靶标和相机的相对距离成正比，光轴方向的测量误差与相对距离的平方成正比；图像中提取的特征点的位置误差是测量系统误差的主要来源，位置误差包括特征点提取误差和由于镜头畸变等引起的特征点成像位置偏移；长焦距和小像元有助于减小相机的量化误差；焦距的标定误差和靶标尺寸主要影响光轴方向的距离测量精度，对其余两个方向的精度影响不大；测量系统的解算算法不是引入误差的主要因素。

Abstract

On the theoretical analysis

the six factors relating to the measuring precision of a monocular vision pose measurement system with three corresponding feature points were investigated.These factors are the distance between marker and camera

size of the marker

quantitative errors of camera

calibration errors of intrinsic parameters of camera

position errors of feature points

and the error introduced by pose estimation algorithm. The simulations and imaging experiments were performed to verify the validity of the theoretical analysis. It shows that the most effective factor is the measuring distance. The longer focal length and smaller size of a pixel on CCD can reduce the quantitative error

and the bigger error size of target can improve the precision of feature extraction and can minimize the impaction of extraction error caused by image processing algorithm. The noise introduced by electronic hardware is also an important factor that can not be ignored during the system designing phase. The focal length

position of intersection of optical axis and the image plane on CCD

aberrations of lenses of the camera should be calibrated after the camera is manufactured during the calibration phase

and the error of calibration is the second significant factor for the whole measurement system. The error introduced by pose estimation algorithm can be ignored because it is much smaller than the whole errors. The position errors of feature points extracted from the image is the main impaction of precision loss of system.

关键词

Keywords

references

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