🚀 Floyd-Machine: Centralized Robotic Control System

Welcome to the Machine
Floyd-Machine is a centralized control system designed to coordinate and optimize the performance of autonomous robots using advanced artificial intelligence. This project integrates virtual simulation with real-world deployment, achieving efficient and adaptable real-time control.

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🧠 Project Vision

Floyd-Machine oversees and coordinates multiple autonomous robots, optimizing their performance across various tasks and environments.

Key Objectives:

• Design an advanced simulation environment.
• Implement intelligent algorithms for autonomous tasks.
• Deploy a functional system in the real world with robustness and adaptability.

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📦 Project Phases

Phase 0: Project Structure

• Objective: Establish the organizational foundation of the project.
• Actions:
  • Selection of Key Libraries:
    • 🟢 OpenGL: 3D graphics rendering.
    • 🟢 GLAD: OpenGl Manager.
    • 🟢 Arduino: To make the robots
  • Code Structuring:
    • Create a modular system for future scalability.
    • Design an adaptable architecture with support for AI and real-time simulation.

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Phase 1: Testing Environment

• Objective: Develop a virtual environment for simulation and training.
• Subphases:
  1. 3D Real-World Simulator:
     • Create a 3D environment that replicates real-world physical and environmental conditions.
  2. Basic Robot Representation:
     • Design initial robot models.
     • Provide terminal-based and graphical simulation representations.
  3. Environment Perception (Cameras and Sensors):
     • Implement virtual cameras and sensors.
     • Train robots in basic tasks like navigation and manipulation.

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Phase 2: Mini Real Version

• Objective: Transition developments from the virtual environment to the physical world.
• Actions:
  • Integrate hardware and software for real-world operation.
  • Design and test the centralized control tower.
  • Validate the system under real-world conditions.

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🛠️ Technologies and Libraries

Main Libraries Used

• OpenGL: For advanced 3D rendering.
• GLAD: OpenGL Manager. to
• Arduino: Microcontroller

Other Tools (Evolving)

• Physical simulation systems.
• Frameworks for machine learning and artificial intelligence.

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🚧 Roadmap

• ✅ Establish the basic project structure.
• ⬜ Develop the 3D environment simulator.
• ⬜ Create initial robot models.
• ⬜ Implement virtual sensors and cameras.
• ⬜ Test integration and deploy to physical hardware.
• ⬜ Optimize the centralized control tower.

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🚀 How To build

• How to build

📚 How to Contribute

Interested in contributing?
Follow these steps:

1. Fork this repository.
2. Create your branch (git checkout -b feature/new-feature).
3. Commit your changes (git commit -m "Added new feature").
4. Push to your branch (git push origin feature/new-feature),
5. Open a pull request and you're all set! 🚀

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JARVIS: GitHub Repository

💬 Contact

For questions, suggestions, or ideas, feel free to contact us:
📧 Email: [email protected]

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📝 License

This project is licensed under the Apache-2.0 license.
See the LICENSE file for more details.