Image-Based Deep Reinforcement Meta-Learning for Autonomous Lunar Landing
Future exploration and human missions on large planetary bodies (e.g., moon, Mars) will require advanced g...
Posts by Tag
- RL 6
- Relative Motion 3
- PINN 3
- ZEM/ZEV 2
- Lyapunov Vector Fields 2
- Landing 2
- Computer Vision 2
- Planetary Landing 1
- Computer vision 1
RL
Safe Lunar landing via images: A Reinforcement Meta-Learning application to autonomous hazard avoidance and landing
Ground view, segmentation mask ...
Adaptive generalized ZEM-ZEV feedback guidance for planetary landing via a deep reinforcement learning approach
Precision landing on large and small planetary bodies is a techno...
Image-based deep reinforcement learning for autonomous lunar landing
Digital terrain model and rendered view Future missions to...
ELM-based Actor-Critic Approach to Lyapunov Vector Fields Relative Motion Guidance in Near-Rectilinear Orbit
Trajectory and Lyapunov vector field In this paper, we present a new feedback guidance algorithm f...
Actor-critic reinforcement learning approach to relative motion guidance in near-rectilinear orbit
Trajectories This paper aims a developing a new feedback gui...
Relative Motion
Image-based deep reinforcement learning for autonomous lunar landing
Digital terrain model and rendered view Future missions to...
ELM-based Actor-Critic Approach to Lyapunov Vector Fields Relative Motion Guidance in Near-Rectilinear Orbit
Trajectory and Lyapunov vector field In this paper, we present a new feedback guidance algorithm f...
Actor-critic reinforcement learning approach to relative motion guidance in near-rectilinear orbit
Trajectories This paper aims a developing a new feedback gui...
PINN
Orbit determination via physics informed neural networks
Estimated trajectories This paper introduces a method for solving orbit determination problems named Physics Informed Orbit Determinatio...
Orbit determination via physics informed neural networks in cislunar environment
Estimated trajectories The approach presented in this paper is based on using Physics Informed Ne...
Orbit determination via physics informed neural networks
Estimated trajectories ...
ZEM/ZEV
Adaptive generalized ZEM-ZEV feedback guidance for planetary landing via a deep reinforcement learning approach
Precision landing on large and small planetary bodies is a techno...
Actor-critic reinforcement learning approach to relative motion guidance in near-rectilinear orbit
Trajectories This paper aims a developing a new feedback gui...
Lyapunov Vector Fields
Image-based deep reinforcement learning for autonomous lunar landing
Digital terrain model and rendered view Future missions to...
ELM-based Actor-Critic Approach to Lyapunov Vector Fields Relative Motion Guidance in Near-Rectilinear Orbit
Trajectory and Lyapunov vector field In this paper, we present a new feedback guidance algorithm f...
Landing
Image-Based Deep Reinforcement Meta-Learning for Autonomous Lunar Landing
Future exploration and human missions on large planetary bodies (e.g., moon, Mars) will require advanced g...
Safe Lunar landing via images: A Reinforcement Meta-Learning application to autonomous hazard avoidance and landing
Ground view, segmentation mask ...
Computer Vision
Image-Based Deep Reinforcement Meta-Learning for Autonomous Lunar Landing
Future exploration and human missions on large planetary bodies (e.g., moon, Mars) will require advanced g...
Safe Lunar landing via images: A Reinforcement Meta-Learning application to autonomous hazard avoidance and landing
Ground view, segmentation mask ...
Planetary Landing
Adaptive generalized ZEM-ZEV feedback guidance for planetary landing via a deep reinforcement learning approach
Precision landing on large and small planetary bodies is a techno...
Computer vision
VisualEnv: visual Gym environments with Blender
VisualEnv is a tool designed for creating visual environment for reinforcement learning. It is the product of an integration of an open-source modelling an...