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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| Published in | International journal of automation and computing Vol. 14; no. 2; pp. 147 - 158 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Beijing
Institute of Automation, Chinese Academy of Sciences
01.04.2017
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | 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%. |
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| AbstractList | 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%. 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%. |
| Author | Ying Xie Xiang-Dong Yang Zhi Liu Shu-Nan Ren Ken Chen |
| AuthorAffiliation | Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Beijing 100084, China State Key Laboratory of Tribology, Beijing 100084, China |
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| Copyright | Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2017 Copyright Springer Science & Business Media 2017 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2017. |
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| DocumentTitleAlternate | Method for Visual Localization of Oil and Gas Wellhead Based on Distance Function of Projected Features |
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| Keywords | 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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| Notes | 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%. |
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| Publisher | Institute of Automation, Chinese Academy of Sciences Springer Nature B.V |
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| SubjectTerms | 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 |
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| Title | Method for Visual Localization of Oil and Gas Wellhead Based on Distance Function of Projected Features |
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