Convolutional Neural Network-Based Spacecraft Attitude Control for Docking Port Alignment

被引:0
|
作者
Kim, Sang-Hyeon [1 ]
Choi, Han-Lim [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Dept Aerosp Engn, Daejeon 305701, South Korea
基金
新加坡国家研究基金会;
关键词
Spacecraft attitude control; Convolutional Neural Networks (CNNs); Three-dimensional spacecraft simulator;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes the spacecraft attitude control algorithm based on Convolutional Neural Networks (CNNs) for spacecraft's docking port alignment. the CNN model is used in order to recognize the attitude of target spacecraft and the attitude controller aligns the docking port of the target spacecraft using the target spacecraft's attitude information obtained from CNN. Three-Dimensional spacecraft simulator is developed for training CNN model and testing the algorithm. Experiments are conducted for demonstrating the target spacecraft's attitude recognition and attitude control performances of the proposed algorithm.
引用
收藏
页码:484 / 489
页数:6
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