HayatPMT

🚀 Autonomous-UAV-Navigation-System - Navigate Drones with Ease

📋 Overview

The Autonomous UAV Navigation System enables drones to fly autonomously in complex urban environments. This system uses real-time mapping, global path planning, and sensor fusion for safe navigation. With integration into ROS 2, PX4 Offboard control, and Gazebo simulation, this tool allows for high-fidelity testing and deployment.

🎯 Key Features

• 2.5D Occupancy-Grid Mapping: Visualize the environment in real-time to understand obstacles and pathways.
• A* Global Path Planning: Choose the best route for the drone to reach its destination.
• Dynamic Obstacle Avoidance: React to moving obstacles effectively to ensure safety during flight.
• Depth and LiDAR Sensor Fusion: Combine data from multiple sensors for improved accuracy in navigation.
• Full Integration with ROS 2 and PX4: Seamlessly interface with modern communication protocols for robust control.

🚀 Getting Started

To get started with the Autonomous UAV Navigation System, follow these steps:

1. Download the Software:
   • Visit this page to download: GitHub Releases Page
2. Install Dependencies:
   • Ensure that you have the necessary software to run this application. You will need:
     • Python 3.x: Most recent version preferred. Download from python.org.
     • ROS 2: Follow the installation guide available on the ROS 2 website ros.org.
     • PX4 Autopilot: Install PX4 following the guidelines at px4.io.
     • Gazebo Simulator: Get Gazebo from gazebosim.org.
3. Setup the Environment:
   • After installing the above dependencies, you may need to set up your environment variables. Refer to the installation guides for ROS 2 and PX4 for complete instructions.

📥 Download & Install

• Visit this page to download the latest version: GitHub Releases Page.
• Choose the appropriate version for your system and click to download.

🛠️ System Requirements

To ensure smooth operation, check the following minimum requirements:

• Operating System: Windows 10 or later, macOS Catalina or later, or Ubuntu 20.04 LTS or later.
• RAM: Minimum of 8 GB.
• Processor: Quad-core Intel or AMD processor.
• Storage: At least 5 GB of free disk space.

⚙️ Running the Application

1. Navigate to the Installation Directory:
   • Open your terminal (Command Prompt, PowerShell, or equivalent) and change the directory to where the software is installed.
2. Launch the Software:
   • Use the command:

     python3 autopilot.py
     

   • This will start the navigation system.
3. Connect to Your Drone:
   • Ensure your drone is powered on and connected to your computer. The software will recognize the connection and begin the navigation process.
4. Start Testing:
   • Use the GUI to choose your target location. Monitor the real-time mapping and observe how the drone navigates and avoids obstacles.

🛡️ Troubleshooting

If you encounter any issues:

• Error Messages: Refer to the console output for error messages that may indicate missing libraries or connection issues.
• Dependencies Not Found: Ensure all dependencies are correctly installed and updated.
• No GUI Display: Make sure your display driver is up to date and supports OpenGL.

💬 Community Support

For questions and support, join our community:

• GitHub Issues Page: Report Issues Here
• Discussion Forum: Engage with other users and developers for tips and advice.

🔗 Contributing

We welcome contributions to the Autonomous UAV Navigation System. If you have suggestions or enhancements, feel free to submit a pull request or open an issue on GitHub.

🏷️ Topics

This project covers various topics including:

• astar-algorithm
• autonomous-drones
• depth-camera
• lidar
• obstacle-avoidance
• and many more related fields.

Explore and learn more about the technologies involved in this project to enhance your understanding and use of the application.

Stay connected through the GitHub page to receive updates and new features as they are developed.