AI-Optimized Trajectory Planning
July 20, 2025 • By Dr. Lena Torres • 9 min read
AI Research
Trajectory Planning
July 20, 2025 • By Dr. Lena Torres • 9 min read
Our new AI-powered trajectory optimization engine redefines how we plan satellite operations. Combining deep learning with astrodynamics, we've developed a system that calculates mission-critical paths with unprecedented precision and speed.
Trained on millions of trajectories to predict optimal paths
Guarantees feasibility of all generated orbits
Adjusts to changing orbital conditions instantly
Visualization of AI-generated orbital paths over time
Our AI plans synchronized passes for satellite constellations, maximizing coverage while avoiding conflicts.
The system calculates on-the-fly corrections for unexpected orbital disturbances.
The system uses convolutional networks to process orbital elements and recurrent layers for temporal prediction.
// Neural network input
{
"semi_major_axis": 7000,
"inclination": 51.6,
"eccentricity": 0.001,
"time_remaining": 3600
}
We enforce physical constraints through a penalty-based training approach to ensure realistic and safe orbits.
// Constraint violation calculation
if distance < 5000: # meters
add_penalty(1000 * (5000/distance - 1))
