A survey on artificial intelligence trends in spacecraft guidance dynamics and control
The rapid developments of artificial intelligence in the last decade are influencing aerospace
engineering to a great extent and research in this context is proliferating. We share our …
engineering to a great extent and research in this context is proliferating. We share our …
[HTML][HTML] Deep learning and artificial neural networks for spacecraft dynamics, navigation and control
The growing interest in Artificial Intelligence is pervading several domains of technology and
robotics research. Only recently has the space community started to investigate deep …
robotics research. Only recently has the space community started to investigate deep …
Reinforcement learning in dual-arm trajectory planning for a free-floating space robot
A free-floating space robot exhibits strong dynamic coupling between the arm and the base,
and the resulting position of the end of the arm depends not only on the joint angles but also …
and the resulting position of the end of the arm depends not only on the joint angles but also …
Deep reinforcement learning for spacecraft proximity operations guidance
This paper introduces a guidance strategy for spacecraft proximity operations, which
leverages deep reinforcement learning, a branch of artificial intelligence. This technique …
leverages deep reinforcement learning, a branch of artificial intelligence. This technique …
Optimality principles in spacecraft neural guidance and control
This Review discusses the main results obtained in training end-to-end neural architectures
for guidance and control of interplanetary transfers, planetary landings, and close-proximity …
for guidance and control of interplanetary transfers, planetary landings, and close-proximity …
Deep reinforcement learning for rendezvous guidance with enhanced angles-only observability
H Yuan, D Li - Aerospace Science and Technology, 2022 - Elsevier
This research studies the application of reinforcement learning in spacecraft angles-only
rendezvous guidance in the presence of multiple constraints and uncertainties. To apply a …
rendezvous guidance in the presence of multiple constraints and uncertainties. To apply a …
Autonomous Maneuver Planning for Small-Body Reconnaissance via Reinforcement Learning
Z Chen, H Cui, Y Tian - Journal of Guidance, Control, and Dynamics, 2024 - arc.aiaa.org
This paper presents a reinforcement learning (RL) based approach for autonomous
maneuver planning of low-altitude flybys for site-specific reconnaissance of small bodies …
maneuver planning of low-altitude flybys for site-specific reconnaissance of small bodies …
On the fate of slow boulders ejected after DART impact on Dimorphos
F Moreno, G Tancredi, AC Bagatin - The Planetary Science …, 2024 - iopscience.iop.org
Abstract On 2022 September 26 23: 14 UT, the NASA Double Asteroid Redirection Test
spacecraft successfully impacted Dimorphos, the secondary component of the binary …
spacecraft successfully impacted Dimorphos, the secondary component of the binary …
Propulsionless planar phasing of multiple satellites using deep reinforcement learning
This work creates a framework for solving highly non-linear satellite formation control
problems by using model-free policy optimisation deep reinforcement learning (DRL) …
problems by using model-free policy optimisation deep reinforcement learning (DRL) …
Small bodies non-uniform gravity field on-board learning through Hopfield Neural Networks
Small bodies environment is usually difficult to be modelled for a number of reasons. Among
the others, the uncertainty associated to the non-uniform gravitational field requires in-situ …
the others, the uncertainty associated to the non-uniform gravitational field requires in-situ …