The field of satellite communication and maneuverability is witnessing significant advancements, driven by the increasing need for enhanced autonomy and agility in space. Researchers are exploring innovative approaches to improve satellite safety and sustainability, such as the use of Reinforcement Learning (RL) for training optimal adversary avoidance algorithms and developing multi-agent RL environments for realistic orbital dynamics simulations. Another key area of focus is the optimization of satellite communication systems, including the development of video-aware mobility management frameworks and joint optimization of handoff and video rate in LEO satellite networks. Noteworthy papers in this area include:

• I Can Hear You Coming: RF Sensing for Uncooperative Satellite Evasion, which presents a novel approach to utilizing intercepted radio frequency communication and dynamic spacecraft state for training adversary avoidance algorithms.
• OrbitZoo: Multi-Agent Reinforcement Learning Environment for Orbital Dynamics, which introduces a versatile multi-agent RL environment for realistic data generation and validation against real-world satellite constellations.