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Method for Visual localization of Oil and Gas Wellhead Based on distance Function of Projected Features

International Journal of Automation and computing 2017年第2期14卷 147-158页

作者： Ying Xie Xiang-dong Yang Zhi Liu Shu-Nan Ren Ken Chen 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

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%.

关键词： Robot vision visual localization 3d object localization model based pose estimation distance function of projectedfeatures nonlinear least squares random sample consensus (RANSAC).

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