Department of Communication and Navigation, International University of Rabat, Rabat, Morocco
Mini Review
Control, Navigation and Dynamics of Spacecraft Using Artificial Neural Networks and Deep Learning
Author(s): Stefano Silvestrini*
Several areas of technology and robotics research are being influenced by an increasing interest in AI. The space community has only recently
begun to investigate artificial neural networks and deep learning techniques for space systems. The most important aspects of these topics for
controlling, guiding, and navigating spacecraft dynamics will be discussed in this paper. In an effort to draw attention to the benefits and drawbacks
of employing the most prevalent architectures of artificial neural networks and the training strategies that go along with them, we examine these
components. Quantitative and qualitative metrics are used to compare and review particular system identification, control synthesis, and optical
navigation applications of artificial neural networks. The end-to-end deep learning frameworks for spacecraft guidance, navigation, and control are
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DOI:
10.37421/2329-6542.2023.11.258
Astrophysics & Aerospace Technology received 114 citations as per Google Scholar report