Deep reinforcement learning spacecraft guidance with state uncertainty for autonomous shape reconstruction of uncooperative target-Reference-Cited by-同舟云学术

Deep reinforcement learning spacecraft guidance with state uncertainty for autonomous shape reconstruction of uncooperative target

Published:2023-07 Issue: Volume: Page:
ISSN:0273-1177
Container-title:Advances in Space Research
language:en
Short-container-title:Advances in Space Research

Author:

Brandonisio Andrea,Capra Lorenzo,Lavagna Michèle

Funder

Fondazione Fratelli Confalonieri

Publisher

Elsevier BV

Subject

Space and Planetary Science,Aerospace Engineering,General Earth and Planetary Sciences,Atmospheric Science,Geophysics,Astronomy and Astrophysics

Reference31 articles.

1. Managing engineering systems with large state and action spaces through deep reinforcement learning;Andriotis;Reliab. Eng. Syst. Saf.,2019

2. Brandonisio, A., Lavagna, M., 2021. Sensitivity analysis of adaptive guidance via deep reinforcement learning for uncooperative space objects imaging. In: 2021 AAS/AIAA Astrodynamics Specialist Conference, Big Sky, Montana, USA, pp. 1–20.

3. Reinforcement learning for uncooperative space objects smart imaging path-planning;Brandonisio;J. Astronaut. Sci.,2021

4. Network architecture and action space analysis for deep reinforcement learning towards spacecraft autonomous guidance;Capra;Adv. Space Res.,2023

5. Chan, D.M., Agha-mohammadi, A.-A., 2019. Autonomous imaging and mapping of small bodies using deep reinforcement learning. In: 2019 IEEE Aerospace Conference, Big Sky, Montana, USA, pp. 1–12, https://doi.org/10.1109/AERO.2019.8742147.

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