Project Status Note
Results based on internal simulation and testing environments.
The Challenge
Calculating efficient transfer orbits for large constellations typically requires immense computational resources and hours of processing time, making real-time adjustments challenging during critical maneuvers.
The Solution
We developed a hybrid AI-physics engine that pre-computes orbital manifolds and uses a reinforcement learning agent to find optimal paths in milliseconds. The interface allows mission controllers to visualize potential collisions and fuel usage in real-time.
The Outcome
Demonstrated potential for significant fuel savings in simulation environments. Currently being evaluated for pilot deployment opportunities.