Cyber-Resilient Satellite Collision Avoidance via Deep Reinforcement Learning: An End-to-End PPO Framework with Adversarial Robustness
An AI-driven research project developing an autonomous satellite collision avoidance framework for Low Earth Orbit (LEO) using Deep Reinforcement Learning and Proximal Policy Optimization (PPO). The system enables intelligent, fuel-efficient maneuver planning while enhancing resilience against adversarial cyber threats, contributing to safer and more autonomous satellite operations.