Inspiration : India’s expanding space ecosystem and student interest in aerospace motivated us to simplify rocket trajectory learning. TrajectAI makes complex physics visual, interactive, and accessible.
What it does : TrajectAI simulates rocket launches and compares a user-defined trajectory with an AI-optimized launch angle. It visualizes altitude, distance, and fuel efficiency in real time.
How we built it : Built using Python + Streamlit for UI, NumPy for physics simulation, and Matplotlib for visualization. Optimization is done using algorithmic search, not heavy ML.
Challenges we ran into : Balancing realism with simplicity, ensuring fair fuel efficiency comparison, and keeping simulations fast and responsive for real-time interaction.
Accomplishments that we're proud of : Created a lightweight, interactive rocket optimization tool that clearly demonstrates AI-driven performance improvement through visualization.
What we learned : Learned how physics simulations and AI optimization work together, along with performance tuning and effective technical visualization.
What's next for TrajectAI : Add real-world constraints, data-driven optimization, 3D trajectories, and deeper AI integration for education and early-stage space innovation.
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