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清华大学学报(自然科学版)  2018, Vol. 58 Issue (4): 411-416    DOI: 10.16511/j.cnki.qhdxxb.2018.26.023
  机械工程 本期目录 | 过刊浏览 | 高级检索 |
基于双PSD的三维测量系统的标定方法
郑军, 李文庆
清华大学 机械工程系, 先进成形制造教育部重点实验室, 北京 100084
Calibration of 3-D measurement system based on a double position sensitive detectors
ZHENG Jun, LI Wenqing
Key Laboratory of Materials Processing Technology of the Ministry of Education, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
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摘要 双目视觉已在机器人视觉、三维测量等多个领域得到广泛应用。但是,随着研究的不断深入,双目视觉的局限性也逐渐突显出来。例如测量复杂形面的三维形貌精度低,计算速度慢等。基于此,该文提出一种基于双光敏位置探测器(position sensitive detector,PSD)的三维测量方法。利用2个PSD从不同的角度捕获、跟踪激光点的方式来还原工件的三维信息,省去了传统双目视觉中的特征点识别和匹配部分,极大简化了三维测量模型。由于传统的标定方法不再适用,该文提出2种标定方案,改进的Faugeras标定加LM(Levenberg-Marquardt)优化方法和BP(back propagation)神经网络方法。通过对比实验分析,改进的Faugeras标定加LM优化的方法能达到更高更稳定的三维测量精度。
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郑军
李文庆
关键词 三维测量光敏位置探测器Faugeras标定方法LM(Levenberg-Marquardt)优化BP(back propagation)神经网络    
Abstract:Binocular vision systems have been widely used in many areas. Traditional calibration methods for binocular vision systems commonly use many complicated mathematical models, which result in low precision and speed. This paper presents a fast measurement method based on double position sensitive detectors (PSDs). Two detectors are aimed from different angles to detect the position of the laser point for the 3D measurement. The 3-D measurement is greately simplified by replacing a charge coupled device (CCD) with a PSD. Since this method is fundamentally different from traditional methods, the normal calibration methods are no longer applicable. Thus, this article presents two calibration methods respectively using an improved Faugeras calibration combined with Levenberg-Marquardt (LM) arithmetic optimization and a back propagation (BP) neural network. Tests show that the LM optimization gives better accuracy and stability.
Key words3-D measurement    position sensitive detector    Faugeras calibration    Levenberg-Marquardt arithmetic optimization    back propagation neural networks
收稿日期: 2017-11-17      出版日期: 2018-04-15
ZTFLH:  TP391.41  
基金资助:“高档数控机床与基础制造装备”科技重大专项(2015ZX04005006)
作者简介: 郑军(1971-),男,副研究员。E-mail:zhengj@tsinghua.edu.cn
引用本文:   
郑军, 李文庆. 基于双PSD的三维测量系统的标定方法[J]. 清华大学学报(自然科学版), 2018, 58(4): 411-416.
ZHENG Jun, LI Wenqing. Calibration of 3-D measurement system based on a double position sensitive detectors. Journal of Tsinghua University(Science and Technology), 2018, 58(4): 411-416.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2018.26.023  或          http://jst.tsinghuajournals.com/CN/Y2018/V58/I4/411
  图1 二维 PSD结构图
  图2 双 PSD系统成像模型
  图3 典型三层 BP神经网络结构
  图4 双 PSD平台
  表1 方案1标定结果内部参数
  表2 方案1标定结果外部参数
  图5 方案1关于Z=0平面坐标x、y、z的误差拟合曲面
  图6 方案2关于Z=0平面坐标x、y、z的误差拟合曲面
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