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基于同轴约束的锥套单目视觉位置与姿态估计方法

Monocular Visual Position and Attitude Estimation Method of a Drogue Based on Coaxial Constraints.

作者信息

Zhao Kedong, Sun Yongrong, Zhang Yi, Li Hua

机构信息

Navigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

出版信息

Sensors (Basel). 2021 Aug 23;21(16):5673. doi: 10.3390/s21165673.

DOI:10.3390/s21165673
PMID:34451114
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8402363/
Abstract

In aerial refueling, there exists deformation of the circular feature on the drogue's stabilizing umbrella to a certain extent, which causes the problem of duality of position estimation by a single circular feature. In this paper, a monocular visual position and attitude estimation method of a drogue is proposed based on the coaxial constraints. Firstly, a procedure for scene recovery from one single circle is introduced. The coaxial constraints of the drogue are proposed and proved to be useful for the duality's elimination by analyzing the matrix of the spatial structure. Furthermore, we came up with our method, which is composed of fitting the parameters of the spatial circles by restoring the 3D points on it, using the two-level coaxial constraints to eliminate the duality, and optimizing the normal vector of the plane where the inner circle is located. Finally, the effectiveness and robustness of the method proposed in this paper are verified, and the influence of the coaxial circle's spatial structure on the method is explored through simulations of and experiments on a drogue model. Under the interference of a large amount of noise, the duality elimination success rate of our method can also be maintained at a level that is more than 10% higher than others. In addition, the accuracy of the normal vector obtained by the fusion algorithm is improved, and the mean angle error is reduced by more than 26.7%.

摘要

在空中加油过程中,锥套稳定伞上的圆形特征会存在一定程度的变形,这导致了利用单一圆形特征进行位置估计时出现双义性问题。本文提出了一种基于同轴约束的锥套单目视觉位置和姿态估计方法。首先,介绍了从单个圆进行场景恢复的过程。通过分析空间结构矩阵,提出了锥套的同轴约束,并证明其对消除双义性是有用的。此外,我们提出了自己的方法,该方法包括通过恢复空间圆上的三维点来拟合空间圆的参数,利用两级同轴约束消除双义性,并优化内圆所在平面的法向量。最后,验证了本文所提方法的有效性和鲁棒性,并通过锥套模型的仿真和实验,探讨了同轴圆空间结构对该方法的影响。在大量噪声干扰下,我们的方法的双义性消除成功率也能保持在比其他方法高出10%以上的水平。此外,融合算法得到的法向量精度得到提高,平均角度误差降低了26.7%以上。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/f8fdcf6497a3/sensors-21-05673-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/0e2cec2ead5b/sensors-21-05673-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/c599d36c010e/sensors-21-05673-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/21a3ec541f41/sensors-21-05673-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/131bbcd65201/sensors-21-05673-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/c9ff65689eb6/sensors-21-05673-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/71f1c7d26a09/sensors-21-05673-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/8e2f1c19a67d/sensors-21-05673-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/22a9effe8621/sensors-21-05673-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/aeb3d0a8cc2f/sensors-21-05673-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/f8fdcf6497a3/sensors-21-05673-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/0e2cec2ead5b/sensors-21-05673-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/c599d36c010e/sensors-21-05673-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/21a3ec541f41/sensors-21-05673-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/131bbcd65201/sensors-21-05673-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/c9ff65689eb6/sensors-21-05673-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/71f1c7d26a09/sensors-21-05673-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/8e2f1c19a67d/sensors-21-05673-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/22a9effe8621/sensors-21-05673-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/aeb3d0a8cc2f/sensors-21-05673-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3e5/8402363/f8fdcf6497a3/sensors-21-05673-g010.jpg

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