TrajGPT: Beyond Low Earth Orbit Trajectory Generation via Machine Learning

Ensuring a deep space crew can arrive at their destination at the appropriate time and return safely requires detailed planning. Current design methods involve generating millions of trajectories and analyzing countless permutations of variables such as launch date and time, propellant budgets, and abort options (too complex to be done onboard in real-time). Project will utilize machine learning to investigate methods which could replace current, brute-force physics-based modeling with big data techniques, which could unlock breakthroughs in crew autonomy and operational flexibility. ​

If the model proves workable, the general capability could be broadly applicable to both crewed and uncrewed missions involving spaceflight. ​ For crewed missions, a change in modeling techniques may enable onboard capabilities that could improve crew autonomy and operational flexibility, vital to the success of future Mars missions.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.