Review of advanced guidance and control algorithms for space/aerospace vehicles

R Chai, A Tsourdos, A Savvaris, S Chai, Y Xia… - Progress in Aerospace …, 2021 - Elsevier
The design of advanced guidance and control (G&C) systems for space/aerospace vehicles
has received a large amount of attention worldwide during the last few decades and will …

Motion planning for mobile robots—Focusing on deep reinforcement learning: A systematic review

H Sun, W Zhang, R Yu, Y Zhang - IEEE Access, 2021 - ieeexplore.ieee.org
Mobile robots contributed significantly to the intelligent development of human society, and
the motion-planning policy is critical for mobile robots. This paper reviews the methods …

Deep reinforcement learning for six degree-of-freedom planetary landing

B Gaudet, R Linares, R Furfaro - Advances in Space Research, 2020 - Elsevier
This work develops a deep reinforcement learning based approach for Six Degree-of-
Freedom (DOF) planetary powered descent and landing. Future Mars missions will require …

Reinforcement learning for robust trajectory design of interplanetary missions

A Zavoli, L Federici - Journal of Guidance, Control, and Dynamics, 2021 - arc.aiaa.org
This paper investigates the use of reinforcement learning for the robust design of low-thrust
interplanetary trajectories in presence of severe uncertainties and disturbances, alternately …

Deep learning and artificial neural networks for spacecraft dynamics, navigation and control

S Silvestrini, M Lavagna - Drones, 2022 - mdpi.com
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 …

Reinforcement learning in spacecraft control applications: Advances, prospects, and challenges

M Tipaldi, R Iervolino, PR Massenio - Annual Reviews in Control, 2022 - Elsevier
This paper presents and analyzes Reinforcement Learning (RL) based approaches to solve
spacecraft control problems. Different application fields are considered, eg, guidance …

Survey of machine learning techniques in spacecraft control design

M Shirobokov, S Trofimov, M Ovchinnikov - Acta Astronautica, 2021 - Elsevier
In this paper, a survey on the machine learning techniques in spacecraft control design is
given. Among the applications of machine learning on the subject are the design of optimal …

Image-based deep reinforcement meta-learning for autonomous lunar landing

A Scorsoglio, A D'Ambrosio, L Ghilardi… - Journal of Spacecraft …, 2022 - arc.aiaa.org
Future exploration and human missions on large planetary bodies (eg, moon, Mars) will
require advanced guidance navigation and control algorithms for the powered descent …

Autonomous closed-loop guidance using reinforcement learning in a low-thrust, multi-body dynamical environment

NB LaFarge, D Miller, KC Howell, R Linares - Acta Astronautica, 2021 - Elsevier
Onboard autonomy is an essential component in enabling increasingly complex missions
into deep space. In nonlinear dynamical environments, computationally efficient guidance …

Run time assured reinforcement learning for safe satellite docking

K Dunlap, M Mote, K Delsing, KL Hobbs - Journal of Aerospace …, 2023 - arc.aiaa.org
Reinforcement learning promises high performance in complex tasks as well as low online
storage and computation cost. However, the trial-and-error learning approach of …