合作靶标标志点检测及位姿测量

葛双龙; 温卓漫; 齐丽君; 邸男; 罗君

doi:10.3788/OPE.20162413.0718

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合作靶标标志点检测及位姿测量

更新时间：2020-08-13

- 合作靶标标志点检测及位姿测量
- Maker detection and pose measurement using a cooperative target
- 光学精密工程 2016年24卷第10s期页码：718-726
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 空军航空大学,吉林长春,130022
  3. 中国科学院大学北京,100049
  4. 吉林警察学院刑事科学技术系,吉林长春,130117
- 作者简介：
- 基金信息：
  
  国家863高技术研究发展计划资助项目（No.2012AA7031010B）()
- DOI：10.3788/OPE.20162413.0718
  中图分类号： TP391.4
- 收稿日期：2016-05-19，
  
  修回日期：2016-06-05，
  
  纸质出版日期：2016-11-14
- 稿件说明：
移动端阅览
葛双龙, 温卓漫, 齐丽君等. 合作靶标标志点检测及位姿测量[J]. 光学精密工程, 2016,24(10s): 718-726

GE Shuang-long, WEN Zhuo-man, QI Li-jun etc. Maker detection and pose measurement using a cooperative target[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 718-726
葛双龙, 温卓漫, 齐丽君等. 合作靶标标志点检测及位姿测量[J]. 光学精密工程, 2016,24(10s): 718-726 DOI： 10.3788/OPE.20162413.0718.

GE Shuang-long, WEN Zhuo-man, QI Li-jun etc. Maker detection and pose measurement using a cooperative target[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 718-726 DOI： 10.3788/OPE.20162413.0718.

摘要

在机械臂抓捕目标时，需要实时求取目标与机械臂上手眼相机之间的相对位姿。本文利用被抓取目标上合作靶标标志点的图像坐标，采用P3P算法对相对位姿进行了高精度解算。首先，利用合作靶标上的圆环和直线对靶标进行快速识别，确定靶标在图像中的区域。然后，把靶标区域分为多个相互有重叠的正方形小窗，将每个小窗内的最亮点作为候选点，并利用标志点的圆形特征，使用多种条件剔除非法点，保留三个合法标志点，最终确定标志点的中心坐标。最后，结合摄像机内参和靶标尺寸信息，用P3P算法求解相对位姿。仿真结果表明，标志点识别的准确率高于99%；位姿解算的旋转误差小于0.1度，平移误差小于0.5 mm。在实验中，上述参数分别为97%、0.2度和1 mm。该算法操作简单、速度快、准确率高、精度高，适用于工业、农业、航空航天等领域的高精度实时单目位姿测量。

Abstract

When mechanical arm arrests target

relative pose between target and hand-eye camera of arm is required to be obtained with real-time. By using image coordinate of mark points of cooperative target

P3P algorithm was adopted to realize high precision calculation of relative pose. Firstly

circles and straight lines of cooperative target were rapidly identified and the area of target circles was determined. Secondly

target area was divided into many square windows with mutually overlapping; with the highlight of each window as candidate point

circular feature of mark point was applied to eliminate illegal points by combining with various conditions

while three legal mark points were kept so as to determine center coordinates of the mark point finally. Lastly

combine with dimension information of participated target in camera and obtain relative pose with P3P algorithm. Simulation results show that the accuracy rate of the mark point identification is higher than 99%; rotation error of pose calculation is less than 0.1°; translation error is less than 0.5mm. In actual experiment

the above parameters respectively are 97%

0.2° and 1mm. Operation of the algorithm is simple with high speed

high accuracy and high precision

applicable to high accuracy real-time monocular pose measurement of industry

agriculture

aerospace and other fields.

关键词

Keywords

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