This paper presents and analyzes Reinforcement Learning (RL) based approaches to solve
spacecraft control problems. Different application fields are considered, eg, guidance …

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 …

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 …

This paper introduces a guidance strategy for spacecraft proximity operations, which
leverages deep reinforcement learning, a branch of artificial intelligence. This technique …

Over the past few years, encouraged by advancements in parallel computing technologies
(eg, Graphic Processing Units, GPUs), availability of massive labeled data as well as …

Real-time guidance is critical for the vertical recovery of rockets. However, traditional
sequential convex optimization algorithms suffer from shortcomings in terms of their poor …

Actively tracking an arbitrary space noncooperative object relied on visual sensor remains a
challenging problem. In this article, we provide an open-source benchmark for space …

Future missions to the Moon and Mars will require advanced guidance navigation and
control algorithms for the powered descent phase. These algorithm should be capable of …

Data analysis methods have scarcely kept pace with the rapid increase in Earth
observations, spurring the development of novel algorithms, storage methods, and …

Precision landing on large planetary bodies is an important technology that enables future
human and robotic exploration of the solar system. For example, over the past decade …