Active Debris Removal (ADR) and Autonomous Rendezvous and Docking (ARD) are essential operations in space missions that enhance safety and sustainability by mitigating space debris and expanding the capabilities of space objects through autonomous operations. ADR focuses on techniques and technologies for capturing and removing space debris, employing methods such as robotic arms, nets, or harpoons to secure defunct satellites and fragments. These measures reduce collision risks and help preserve the orbital environment. The principal considerations for ADR missions include precision navigation, real-time tracking, and effective debris capture mechanisms to address the complexities of varying debris behaviors in space. On the other hand, ARD enables autonomous approaches and docking between spacecraft, requiring sophisticated guidance, navigation, and control systems to perform proximity operations without human intervention. ARD relies on advanced sensors, such as LIDAR and cameras, to ensure accurate position and velocity measurements, allowing for safe docking even in scenarios with potential communication delays. These operations highlight the necessity of coordination between ADR and ARD systems to support future missions that prioritize efficient spacecraft servicing and the maintenance of a sustainable space environment. To enhance mission planning and safety, digital technologies such as virtual reality and agentic AI can be employed to simulate and evaluate security and success levels before launching real operations and these technologies also enable real-time parameter adjustments based on prior knowledge and predefined rules, allowing for optimal decision-making in dynamic and unknown environments. One of the main challenges in space operations is the lack of effective coordination among subsystems. Therefore, this paper describes a robotic debris removal mission, analyzing all relevant constraints and actions to define decision-making profiles within an agentic AI framework. This approach ensures continuous monitoring and security for autonomous missions while considering both technological advancements and sustainability impacts. The objective is to define a workflow for employing agentic AI that validates and modifies decisions to improve and develop novel designs that prevent debris accumulation and extend the operational lifespan of space objects. As these operations involve significant technical complexities, regulatory hurdles, and the need for standardized practices across missions, addressing these challenges presents opportunities for innovation in debris mitigation technologies and autonomous systems. Evaluating and monitoring collaboration among subsystems can drive advancements in safety measures, enhance mission efficiency, and contribute to sustainable space exploration activities.
