Autonomous Space Debris Avoidance Engine

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  auto space debris collision avoidance engine

Inspiration

Building an Autonomous Space Debris Avoidance Engine requires a robust pipeline that can handle real-world orbital data and translate it into actionable maneuvers.

What it does

Build a backend that pull Two-Line Element (TLE) data from public catalogs like Space-Track to predict future positions using the SGP4 algorithm. An AI layer (specifically Reinforcement Learning) can then calculate the most fuel-efficient maneuvers to avoid collisions.

How we built it

Use CesiumJS or Three.js to create a 3D visualization dashboard showing the satellite, incoming debris, and the auto-generated avoidance path.

Challenges we ran into

It has many components, and hard to put together

Accomplishments that we're proud of

ability to complete it as demo

What we learned

learned lots of the space related tech terms and specs

What's next for Autonomous Space Debris Avoidance Engine

continue enhancement

Built With

• docker
• node.js
• python