In this investigation, the integrated attitude and landing control scheme for quadruped robots
in asteroid landing mission scenario is discussed. Compared with the gravitational field …

Reinforcement learning (RL) is used to design impulsive stationkeeping maneuvers for a
spacecraft operating near an L 2 quasi-halo trajectory in a Sun–Earth–Moon point mass …

This paper focuses on the application of meta-reinforcement learning to the robust design of
low-thrust interplanetary trajectories in the presence of multiple uncertainties. A closed-loop …

On-Orbit Servicing (OOS) robots are transforming space exploration by enabling vital
maintenance and repair of spacecraft directly in space. However, achieving precise and safe …

Multi-objective reinforcement learning is used to uncover a subset of the multi-objective
solution space for low-thrust transfers between two L 2 southern halo orbits in the Earth …

To overcome the time-consuming training caused by the sparse reward function in
reinforcement learning, an efficient dense reward framework for robust low-thrust trajectory …

This paper investigates the use of reinforcement learning for the fuel-optimal guidance of a
spacecraft during a time-free low-thrust transfer between two libration point orbits in the …

Future space missions require technological advances to meet more stringent requirements.
Next generation guidance, navigation, and control systems must safely operate …

This paper investigates the performance and computational complexity of recurrent neural
networks (RNNs) trained via meta-reinforcement learning (meta-RL) as onboard spacecraft …

View Video Presentation: https://doi. org/10.2514/6.2023-1439. vid In the last years, several
Artificial Intelligence (AI) application studies have been performed to enhance spacecraft …