A Lightweight Model for Satellite Pose Estimation

被引:4
|
作者
Carcagni, Pierluigi [1 ]
Leo, Marco [1 ]
Spagnolo, Paolo [1 ]
Mazzeo, Pier Luigi [1 ]
Distante, Cosimo [1 ]
机构
[1] CNR ISASI, Ecotekne Campus Via Monteroni Snc, I-73100 Lecce, Italy
关键词
Spacecraft pose estimation; 6DOF pose; Deep learning; Monocular vision; Space imagery;
D O I
10.1007/978-3-031-06427-2_1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work, a study on computer vision techniques for automating rendezvous manoeuvres in space has been carried out. A lightweight algorithm pipeline for achieving the 6 degrees of freedom (DOF) object pose estimation, i.e. relative position and attitude, of a spacecraft in a non-cooperative context using a monocular camera has been studied. In particular, the considered lite architecture has been never exploited for space operations and it allows to be compliant with operational constraints, in terms of payload and power, of small satellite platforms. Experiments were performed on a benchmark Satellite Pose Estimation Dataset of synthetic and real spacecraft imageries specifically introduced for the challenging task of the 6DOF object pose estimation in space. Extensive comparisons with existing approaches are provided both in terms of reliability/accuracy and in terms of model size that ineluctably affect resource requirements for deployment on space vehicles.
引用
收藏
页码:3 / 14
页数:12
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