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Real-time Vision-based Pose Tracking of Spacecraft in Close Range Using Geometric Curve Fitting
IEEE Transactions on Aerospace and Electronic Systems ( IF 5.1 ) Pub Date : 2020-12-01 , DOI: 10.1109/taes.2020.2996074
Chang Liu , Wulong Guo , Weiduo Hu , Rongliang Chena , Jia Liu

This article presents a new framework of real-time vision-based pose tracking for spacecraft in close range using geometric fitting of the imaged geometric primitives (GPs) on the spacecraft. At the first time instant, the tracking is initialized with the template-based pose retrieval and GP-based pose determination. At each subsequent time instant, with the pose prediction from the extended Kalman filter (EKF) as initial value, the GPs are associated with the corresponding image data, and thereby the maximum-likelihood estimation (MLE) for spacecraft pose can be obtained in real time by geometrically fitting the GP projections over the corresponding image data with generalized expectation–maximization and M-estimation. Using the MLE, the EKF generates the final pose estimation and predicts the pose at the next time instant. The basic configurations of the GPs are investigated for the stability of tracking. Sufficient experiments validate the accuracy and the real-time performance of the proposed method.

中文翻译:

基于几何曲线拟合的近距离航天器实时姿态跟踪

本文使用航天器上成像几何基元 (GP) 的几何拟合,提出了一种新的基于实时视觉的航天器近距离姿态跟踪框架。在第一时刻,使用基于模板的姿态检索和基于 GP 的姿态确定来初始化跟踪。在随后的每个时刻,以扩展卡尔曼滤波器(EKF)的姿态预测为初始值,将GP与相应的图像数据相关联,从而可以真实地获得航天器姿态的最大似然估计(MLE)通过使用广义期望最大化和 M 估计在相应的图像数据上几何拟合 GP 投影来计算时间。使用 MLE,EKF 生成最终姿态估计并预测下一时刻的姿态。为了跟踪的稳定性,研究了 GP 的基本配置。足够的实验验证了所提出方法的准确性和实时性。
更新日期:2020-12-01
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