Space Debris

Space debris, encompassing defunct satellites and fragments, poses a significant threat to operational spacecraft and future space exploration. Current research focuses on developing autonomous systems for debris detection, tracking, and removal, employing computer vision techniques (like YOLO and convolutional neural networks), reinforcement learning for optimized mission planning, and machine learning for collision probability prediction and re-entry risk assessment. These advancements aim to improve space situational awareness and enable the development of effective strategies for mitigating the growing space debris problem, ensuring the long-term sustainability of space activities.