Advances in trajectory optimization for space vehicle control
Abstract Space mission design places a premium on cost and operational efficiency. The
search for new science and life beyond Earth calls for spacecraft that can deliver scientific …
search for new science and life beyond Earth calls for spacecraft that can deliver scientific …
[HTML][HTML] 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 …
robotics research. Only recently has the space community started to investigate deep …
Reinforcement learning in spacecraft control applications: Advances, prospects, and challenges
This paper presents and analyzes Reinforcement Learning (RL) based approaches to solve
spacecraft control problems. Different application fields are considered, eg, guidance …
spacecraft control problems. Different application fields are considered, eg, guidance …
Deep learning techniques for autonomous spacecraft guidance during proximity operations
This paper investigates the use of deep learning techniques for real-time optimal spacecraft
guidance during terminal rendezvous maneuvers, in presence of both operational …
guidance during terminal rendezvous maneuvers, in presence of both operational …
Image-based deep reinforcement meta-learning for autonomous lunar landing
Future exploration and human missions on large planetary bodies (eg, moon, Mars) will
require advanced guidance navigation and control algorithms for the powered descent …
require advanced guidance navigation and control algorithms for the powered descent …
A multi-robot path-planning algorithm for autonomous navigation using meta-reinforcement learning based on transfer learning
The adaptability of multi-robot systems in complex environments is a hot topic. Aiming at
static and dynamic obstacles in complex environments, this paper presents dynamic …
static and dynamic obstacles in complex environments, this paper presents dynamic …
Reinforcement learning-based stable jump control method for asteroid-exploration quadruped robots
J Qi, H Gao, H Su, L Han, B Su, M Huo, H Yu… - Aerospace Science and …, 2023 - Elsevier
Unlike the spherical gravitational field of planets and other large solar system bodies, the
gravitational field of asteroids is irregular and weak. It is challenging for a planetary rover to …
gravitational field of asteroids is irregular and weak. It is challenging for a planetary rover to …
On adaptive attitude tracking control of spacecraft: A reinforcement learning based gain tuning way with guaranteed performance
This paper investigates the attitude tracking control problem of a rigid spacecraft subject to
inertial uncertainties, uncertain space perturbations and actuator saturation. Firstly, a static …
inertial uncertainties, uncertain space perturbations and actuator saturation. Firstly, a static …
Meta-reinforcement learning for adaptive spacecraft guidance during finite-thrust rendezvous missions
In this paper, a meta-reinforcement learning approach is investigated to design an adaptive
guidance algorithm capable of carrying out multiple rendezvous space missions …
guidance algorithm capable of carrying out multiple rendezvous space missions …
Image-based meta-reinforcement learning for autonomous guidance of an asteroid impactor
This paper focuses on the use of meta-reinforcement learning for the autonomous guidance
of a spacecraft during the terminal phase of an impact mission toward a binary asteroid …
of a spacecraft during the terminal phase of an impact mission toward a binary asteroid …