Lunar Exploration

Lunar exploration research intensely focuses on developing autonomous navigation and landing systems for robotic missions, employing AI techniques like convolutional neural networks (e.g., YOLOv3, MobileNetV2) and path planning algorithms (e.g., A*, artificial potential fields) to optimize trajectories for various objectives including energy efficiency, risk mitigation, and scientific return. This involves creating robust systems for obstacle detection and avoidance, often integrating extended reality (XR) for improved human-robot interaction and teleoperation. The resulting advancements in autonomous navigation, path planning, and hazard detection are crucial for enabling safer and more efficient lunar missions, expanding our scientific understanding of the Moon and paving the way for future human exploration.