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 …

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 …

In this paper, a novel integrated real-time trajectory planning and tracking control framework
capable of dealing with autonomous ground vehicle (AGV) parking maneuver problems is …

Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …

Precise near-ground trajectory control is difficult for multi-rotor drones, due to the complex
aerodynamic effects caused by interactions between multi-rotor airflow and the environment …

This article focuses on the design, test, and validation of a deep neural network (DNN)-
based control scheme capable of predicting optimal motion commands for autonomous …

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 …

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 …

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 …

We consider the Earth–Venus mass-optimal interplanetary transfer of a low-thrust spacecraft
and show that the optimal guidance can be represented by deep networks in a large portion …