Method for Visual Localization of Oil and Gas Wellhead Based on Distance Function of Projected Features

A localization method based on distance function of projected features is presented to solve the accuracy reduction or failure problem due to occlusion and blurring caused by smog, when dealing with vision based localization for target oil and gas wellhead （OGWH）. Firstly, the target OGWH is modeled...

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Bibliographic Details
Published inInternational journal of automation and computing Vol. 14; no. 2; pp. 147 - 158
Main Authors Xie, Ying, Yang, Xiang-Dong, Liu, Zhi, Ren, Shu-Nan, Chen, Ken
Format Journal Article
LanguageEnglish
Published Beijing Institute of Automation, Chinese Academy of Sciences 01.04.2017
Springer Nature B.V
Subjects
Algorithms
Blurring
CAE) and Design
Computer Applications
Computer-Aided Engineering (CAD
Control
Cylinders
Engineering
Localization
Localization method
Mechatronics
Natural gas
Occlusion
Parameters
Research Article
Robotics
Smog
Synthetic data
Wellheads
井口
参数向量
可视化
图像信息
定位方法
投影特征
油气
距离函数
3D object localization
distance function of projected features
random sample consensus (RANSAC)
model based pose estimation
Robot vision
visual localization
nonlinear least squares
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Summary:A localization method based on distance function of projected features is presented to solve the accuracy reduction or failure problem due to occlusion and blurring caused by smog, when dealing with vision based localization for target oil and gas wellhead （OGWH）. Firstly, the target OGWH is modeled as a cylinder with marker, and a vector with redundant parameter is used to describe its pose. Secondly, the explicit mapping relationship between the pose vector with redundant parameter and projected features is derived. Then, a 2D-point-to-feature distance function is proposed, as well as its derivative. Finally, based on this distance function and its derivative, an algorithm is proposed to estimate the pose of target OGWH directly according to the 2D image information, and the validity of the method is verified by both synthetic data and real image experiments. The results show that this method is able to accomplish the localization in the case of occlusion and blurring, and its anti-noise ability is good especially with noise ratio of less than 70%.
Bibliography:Ying Xie1,2,3 ,Xiang-Dong Yang12,3, Zhi Liu1,2,3 ,Shu-Nan Ren1,2,3 Ken Chena1,2,3 （1 Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China 2 Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Beijing 100084, China 3State Key Laboratory of Tribology, Beijing 100084, China）
Robot vision, visual localization, 3D object localization, model based pose estimation, distance function of projectedfeatures, nonlinear least squares, random sample consensus （RANSAC）.
11-5350/TP
A localization method based on distance function of projected features is presented to solve the accuracy reduction or failure problem due to occlusion and blurring caused by smog, when dealing with vision based localization for target oil and gas wellhead （OGWH）. Firstly, the target OGWH is modeled as a cylinder with marker, and a vector with redundant parameter is used to describe its pose. Secondly, the explicit mapping relationship between the pose vector with redundant parameter and projected features is derived. Then, a 2D-point-to-feature distance function is proposed, as well as its derivative. Finally, based on this distance function and its derivative, an algorithm is proposed to estimate the pose of target OGWH directly according to the 2D image information, and the validity of the method is verified by both synthetic data and real image experiments. The results show that this method is able to accomplish the localization in the case of occlusion and blurring, and its anti-noise ability is good especially with noise ratio of less than 70%.
ISSN:1476-8186
2153-182X
1751-8520
2153-1838
DOI:10.1007/s11633-017-1063-1