AIstronauts: Space Agents on a mission

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Rover

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🌍 Problem:
Navigating a rocket autonomously is a complex challenge. Traditional control systems struggle with precision, stability, and adaptability in dynamic environments. Whether for planetary landings, orbital maneuvers, or interplanetary travel, rockets must follow a precise path while adjusting for external forces like gravity, wind, and system disturbances.

💡 Solution:
We present an autonomous rocket simulation that leverages a PID (Proportional-Integral-Derivative) controller to dynamically adjust thrust and orientation, ensuring precise path-following and stability. The system is coupled with orbital motion simulation, allowing for realistic spaceflight planning and trajectory optimization.

🚀 How It Works:

PID-Controlled Rocket Navigation

Uses real-time feedback to correct deviations from the desired path.
Adjusts thrust and angle dynamically for smooth, efficient trajectory tracking.
Works under different conditions: atmospheric launch, vacuum space maneuvers, and planetary descent.
Orbital Motion Simulation

Implements Keplerian mechanics and numerical integration to predict orbital trajectories.
Models gravitational interactions for accurate spaceflight physics.
Allows testing of satellite placement, docking procedures, and re-entry dynamics.
Autonomous Path-Following Vehicle

Uses AI-based decision-making and PID control to navigate across terrain or space environments.
Can be adapted for planetary rovers, drones, or space-based vehicles.
🎯 Why It Matters:

Space Missions – Enables autonomous course corrections for efficient satellite launches and planetary landings.
AI & Robotics – Advances self-correcting flight and vehicle navigation systems.
Education & Research – Provides an interactive tool for aerospace and AI development.

Autonomous Rocket & Vehicle Simulation for Space Exploration

"Rover team on AIstronauts: Space Agents on a mission Hackathon"

Team Idea

Submission