AI systems proposed to boost launch cadence reliability and traffic management

by Riko Seibo
Tokyo, Japan (SPX) Dec 26, 2025

The global space sector is entering a phase of large-scale satellite constellations and expanded human lunar activity, driving a sharp increase in demand for access to orbit. Within the next two decades, the total mass launched to space is expected to reach several hundred thousand tons, with annual launch counts projected in the tens of thousands and continuing to grow. Launch providers therefore face simultaneous requirements for low cost, high flight rates, and airline-style reliability in space transportation systems.

Reusable launch vehicles have reduced per-flight cost, but they do not yet deliver the launch tempo and reliability needed for this next phase of activity. A study in the Chinese Journal of Aeronautics argues that artificial intelligence applied across launch vehicle life cycles could address these remaining bottlenecks and become a disruptive technology following reusability in space transportation.

The authors outline four main roles for AI in launch systems: agile test and launch preparation, high-reliability flight, rapid maintenance, and efficient safety operation and control. Their goal is an intelligent space transportation system that integrates smart test launches, autonomous flight management, health assessment, and operational control across space and ground segments.

In test and launch preparation, AI-based methods aim to automate inspection, testing, and decision-making so that large launch vehicles can move from checkout to launch on hour-level timelines. When combined with return-to-launch-site capabilities, the system is intended to support re-launch within hours after vehicle recovery, rather than on current multi-day or longer cycles.

During flight, AI-enabled autonomy would handle real-time fault diagnosis, mission replanning, and fault-tolerant control within seconds when anomalies occur. The study suggests that such capabilities could improve flight reliability by 1-2 orders of magnitude even when non-fatal faults arise, by rapidly detecting issues and adjusting guidance and control strategies without waiting for ground intervention.

For post-flight maintenance, the authors propose continuous health monitoring and lifespan prediction for critical components to guide reuse decisions. Reliable and agile health assessment is intended to support maintenance strategies that balance safety and cost while optimizing the reusable lifetime of launch vehicles.

The concept also extends beyond individual vehicles to the broader space-Earth system, where AI would support integrated situational awareness, flight operations scheduling, and coordinated control. This approach targets safe and efficient management of dense launch traffic and on-orbit activity as satellite constellations and debris continue to grow.

The paper notes several challenges that must be addressed before AI can be widely deployed in launch transportation, including tight coupling between subsystems, uncertain failure modes, narrow flight safety corridors, limited sensor data, and the need to process large volumes of heterogeneous information in real time. The authors argue that, despite these obstacles, AI offers significant potential to improve design, manufacturing, and testing through multidisciplinary optimization and reduced reliance on physical testing, further supporting future high-cadence launch architectures.

Research Report:AI Enabled Launch Vehicle: Next Potential Disruptive Technology After Reusability