CelestiaCode

CelestiaCode is a 2D space simulator that visualizes orbits and missions with AI planning, making space exploration fun, interactive, and educational.

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🌌 Inspiration

I’ve always been fascinated by space exploration and mission planning — but most tools are either overly complex or inaccessible to students. I wanted to build something visual, interactive, and smart: a simulator that not only visualizes space but also helps plan missions using AI. That’s how CelestiaCode was born.

🚀 What it does

CelestiaCode is an interactive space exploration simulator that allows users to:

  • Visualize celestial bodies, orbits, and asteroid belts in 2D
  • Simulate multi-body gravitational systems
  • Control spacecraft trajectories
  • Use an AI mission planner (in progress) for optimal flight paths
  • Explore space in a visually engaging environment

🛠 How we built it

  • Core engine built in Python
  • Used Pygame for rendering and UI
  • Simulated gravity using Newtonian mechanics
  • AI module built with scikit-learn and heuristics (MVP stage)
  • Assets created manually and integrated via modular architecture

⚠️ Challenges we ran into

  • Getting multi-body physics to run smoothly in real-time
  • Designing a UI that didn’t distract from the simulation
  • Balancing realism with user-friendly interaction
  • Optimizing performance as more celestial bodies were added

🏆 Accomplishments that we're proud of

  • Built a working 2D space simulator from scratch
  • Integrated asteroid belts and multiple planetary systems
  • Created a functional base for AI-assisted mission planning
  • Designed a beautiful, educational user interface

📚 What we learned

  • Learned to simulate real-world gravitational physics
  • Discovered how to combine AI, visualization, and space mechanics
  • Improved Python, object-oriented programming, and modular design
  • Gained experience in presenting technical ideas visually

🌠 What's next for CelestiaCode

  • Upgrade to 3D visualization using OpenGL or Three.js
  • Expand AI to support reinforcement learning trajectory prediction
  • Add real celestial data import from NASA APIs
  • Implement mission export and data saving features
  • Open-source the project for students and educators

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