Attitude calculation of single camera visual system based on adaptive algorithm

ZHOU Jing; GAO Yin-han; LIU Chang-ying; ZHANG Ye-chi

doi:10.3788/OPE.20122012.2796

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Attitude calculation of single camera visual system based on adaptive algorithm

Article | 更新时间：2020-08-13

- Attitude calculation of single camera visual system based on adaptive algorithm
- Optics and Precision Engineering Vol. 20, Issue 12, Pages: 2796-2803(2012)
- 作者机构：
  
  1. 吉林大学仪器科学与电气工程学院,吉林长春 130022
  2. 吉林农业大学信息技术学院,吉林长春 130118
  3. 吉林大学汽车仿真与控制国家重点实验室,吉林长春 130022
  4. 中国电信有限公司吉林省分公司公众客户部,吉林长春 130033
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20122012.2796
  CLC： TP246;TP391
- Received：25 August 2012，
  
  Revised：17 September 2012，
  
  Published：10 December 2012
- 稿件说明：
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周婧, 高印寒, 刘长英, 张也弛. 基于自适应算法的单目视觉系统的姿态解算[J]. 光学精密工程, 2012,20(12): 2796-2803

ZHOU Jing, GAO Yin-han, LIU Chang-ying, ZHANG Ye-chi. Attitude calculation of single camera visual system based on adaptive algorithm[J]. Editorial Office of Optics and Precision Engineering, 2012,20(12): 2796-2803
周婧, 高印寒, 刘长英, 张也弛. 基于自适应算法的单目视觉系统的姿态解算[J]. 光学精密工程, 2012,20(12): 2796-2803 DOI： 10.3788/OPE.20122012.2796.

ZHOU Jing, GAO Yin-han, LIU Chang-ying, ZHANG Ye-chi. Attitude calculation of single camera visual system based on adaptive algorithm[J]. Editorial Office of Optics and Precision Engineering, 2012,20(12): 2796-2803 DOI： 10.3788/OPE.20122012.2796.

摘要

提出了自适应总体最小二乘算法

以进一步提高单摄像机视觉测量系统光学特征点的姿态解算精度

研究并对比了常用的总体最小二乘算法及自适应总体最小二乘算法在测量系统中的应用。首先

根据空间几何位置关系构建光学特征点、像点及摄像机位置的系统坐标系及三维空间模型

并建立关于光学特征点及像点的矩阵方程。然后

应用常用的总体最小二乘法及自适应总体最小二乘法进行优化求解。最后

基于优化的总体最小二乘解确定光学特征点相对世界坐标系的姿态。应用三坐标测量机进行仿真对比实验

结果表明:常用的总体最小二乘算法得出的姿态坐标的标准差为0.055 7 mm

自适应总体最小二乘算法得出的姿态坐标的标准差为0.041 4 mm。相比之下

自适应总体最小二乘算法有更高的收敛速度及收敛精度

且解算速度优于常用总体最小二乘算法

满足单目视觉测量系统的稳定、可靠和精度高等要求。

Abstract

An adaptive total least square algorithm was proposed to further improve the attitude calculation accuracy of optical characteristic points

and the total least square algorithm and adaptive total least square algorithm were researched and compared. Firstly

the coordinate system and 3D model among optical characteristic points

image points and the position of camera were established according to the space position relationship

and the matrix equation between optical characteristic points and image points was created. Then

the two algorithms mentioned above were used to get an optimization solution. Finally

the attitude of optical characteristic points relative to the word coordinate system was obtained based on the optimization solution. The simulation comparison experiment was performed in a coordinate measuring machine

and the experimental result indicates that the standard tolerance of attitude coordinate calculated by total least squares is 0.055 7 mm

and that by adaptive total least squares is 0.041 4 mm. The compared results show that the adaptive total least square algorithm has higher convergence rate and precision

and its calculation speed is better than that of total least square algorithm. It satisfies the system requirements for stabilization

reliability and high precision.

关键词

Keywords

references

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