🚁 Gesture Controlled Drone Simulation

A real-time drone simulation controlled using hand gestures detected by OpenCV and MediaPipe. This project demonstrates how computer vision can be used as a natural user interface for controlling a virtual drone without a keyboard or joystick.

✨ Features

• 🖐️ Real-time hand tracking using MediaPipe
• 📷 Live webcam input with OpenCV
• 🎮 Gesture-based drone control
• 🚁 Simple drone simulation using Pygame
• ⚡ Low latency and real-time performance
• 🧩 Modular project structure

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🛠️ Tech Stack

Technology	Purpose
Python	Core Programming
OpenCV	Webcam & Image Processing
MediaPipe	Hand Landmark Detection
Pygame	Drone Simulation
NumPy	Numerical Operations

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📂 Project Structure

Gesture-Controlled-Drone/
│__assets_\drone.png
├── main.py                # Main simulation
├── hand_tracking.py       # MediaPipe hand detection
├── gesture.py             # Gesture recognition logic
├── requirements.txt
├── README.md
└── screenshots/

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🚀 Installation

Clone the repository

git clone https://github.com/yourusername/gesture-controlled-drone.git

Go to the project

cd gesture-controlled-drone

Install dependencies

pip install opencv-python mediapipe pygame numpy

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▶️ Run

python main.py

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🎮 Gesture Controls

Gesture	Action
☝️ Index Finger Up	Move Up
👇 Index Finger Down	Move Down
👈 Index Finger Left	Move Left
👉 Index Finger Right	Move Right
✋ No Movement	Hover

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🧠 How It Works

1. OpenCV captures frames from the webcam.
2. MediaPipe detects 21 hand landmarks.
3. The gesture recognition module analyzes landmark positions.
4. Commands are generated based on the index finger location.
5. Pygame updates the drone position in real time.

Webcam
   │
   ▼
OpenCV
   │
   ▼
MediaPipe Hand Tracking
   │
   ▼
Gesture Recognition
   │
   ▼
Drone Controller
   │
   ▼
Pygame Simulation

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📦 Dependencies

• Python 3.10+
• OpenCV
• MediaPipe
• Pygame
• NumPy

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🌟 Planned Features

• ✅ Better gesture recognition
• 🚁 Realistic drone physics
• 🌍 Open-world environment using Three.js
• 🎥 First-person (FPV) camera
• 🎮 Drone takeoff and landing gestures
• 🤖 AI-powered object detection (YOLO)
• 🛰️ GPS and waypoint navigation
• 🌤️ Weather effects
• 🌙 Day/Night cycle
• 🏢 3D buildings and terrain
• 🌐 Web dashboard with FastAPI
• 📱 Mobile gesture control
• 🧭 Autonomous flight mode
• 🎯 Mission system
• ☁️ Cloud data logging

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🤝 Contributing

Contributions are welcome!

1. Fork the repository
2. Create a new branch

git checkout -b feature-name

3. Commit your changes

git commit -m "Added new feature"

4. Push to GitHub

git push origin feature-name

5. Open a Pull Request

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📄 License

This project is licensed under the MIT License.

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👨‍💻 Author

Devraj

• GitHub: https://github.com/devv2308

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