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 …
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 …
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 …
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 …
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 …
Future exploration and human missions on large planetary bodies (eg, moon, Mars) will require advanced guidance navigation and control algorithms for the powered descent …
Onboard autonomy is an essential component in enabling increasingly complex missions into deep space. In nonlinear dynamical environments, computationally efficient guidance …
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 …