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Monocular-based pose determination of uncooperative space objects

机译:单眼的姿势确定不合作空间物体

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摘要

Vision-based methods to determine the relative pose of an uncooperative orbiting object are investigated in applications to spacecraft proximity operations, such as on-orbit servicing, spacecraft formation flying, and small bodies exploration. Depending on whether the object is known or unknown, a shape model of the orbiting target object may have to be constructed autonomously in real-time by making use of only optical measurements. The Simultaneous Estimation of Pose and Shape (SEPS) algorithm that does not require a priori knowledge of the pose and shape of the target is presented. This makes use of a novel measurement equation and filter that can efficiently use optical flow information along with a star tracker to estimate the target's angular rotational and translational relative velocity as well as its center of gravity. Depending on the mission constraints, SEPS can be augmented by a more accurate offline, on-board 3D reconstruction of the target shape, which allows for the estimation of the pose as a known target. The use of Structure from Motion (SfM) for this purpose is discussed. A model-based approach for pose estimation of known targets is also presented. The architecture and implementation of both the proposed approaches are elucidated and their performance metrics are evaluated through numerical simulations by using a dataset of images that are synthetically generated according to a chaser/target relative motion in Geosynchronous Orbit (GEO).
机译:基于视觉的方法,以确定不合作的轨道对象的相对姿势,在应用于航天器接近操作的应用中,例如在轨道维修,航天器形成飞行和小型身体勘探中。取决于对象是已知还是未知的,可以通过仅利用光学测量来实时构造轨道目标对象的形状模型。呈现了不需要先验的姿势和形状的姿势和形状(SEPS)算法的同时估计。这利用了一种新的测量方程和滤波器,可以有效地使用光流信息以及星跟踪器来估计目标角度旋转和平移的相对速度以及其重心。根据使命约束,可以通过更准确的离线,目标形状的电路板3D重建来增强SEP,这允许估计作为已知目标的姿势。讨论了用于此目的的运动(SFM)的结构。还提出了一种基于模型的已知目标姿势估计方法。阐明了所提出方法的架构和实现,并且通过使用根据地球合作用轨道(GEO)中的追逐/目标相对运动的图像数据集来评估通过数值模拟来评估它们的性能度量。

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