Skip to content

Latest commit

 

History

History
52 lines (35 loc) · 2.3 KB

README.md

File metadata and controls

52 lines (35 loc) · 2.3 KB

Swarm 🚁🐝

Welcome to Swarm! This repository is dedicated to exploring and implementing various swarm optimization algorithms and drone control techniques. Whether you're interested in multi-agent pathfinding, collaborative robotics, or autonomous drone systems, this repository will provide insights and code to bring swarm intelligence to life!


Overview 🌐

The Swarm repository is a collection of notebooks, scripts, and resources for:

  • Implementing swarm optimization algorithms such as PSO, ACO, and others 🐜
  • Drone control setups for autonomous behaviors using ArduPilot and SITL 🚁
  • Advanced simulations and multi-agent coordination techniques 🧠
  • Tutorials and in-depth explanations for each algorithm and tool

Contents 📂

Here's what you'll find in this repository:

  • 📘 Tutorials

    • ArduPilot & SITL Installation: A complete setup guide for running drone simulations and manual/automated control.
    • Flight Modes Overview: Jupyter notebooks with detailed explanations of flight modes like Stabilize, Altitude Hold, Loiter, and more.
  • 🤖 Swarm Optimization Algorithms

    • Particle Swarm Optimization (PSO): Code to simulate and visualize the PSO algorithm for multi-agent optimization tasks.
    • Ant Colony Optimization (ACO): Implementation of ACO for pathfinding and shortest-path applications.
    • Other Algorithms: Stay tuned for more swarm intelligence methods and approaches, with insights into their applications in robotics!
  • 🚁 Drone Simulations

    • Autonomous Flight Scripts: Code snippets to set up and run autonomous missions, including formation flying and object detection.
    • Control Command Demos: Commands to control drones in SITL, showcasing modes like Guided, Auto, Loiter, and RTL for multi-agent scenarios.

Getting Started 🚀

  1. Clone the Repo:

    git clone https://github.com/Ahmed-AI-01/Swarm.git
    cd Swarm
  2. Install Requirements:

    • Refer to each tutorial or notebook for installation steps specific to the optimization algorithm or simulation.
  3. Run the Drone Setup:

    • Follow the ArduPilot & SITL Installation guide in the repository for a step-by-step setup to control and test drones virtually.

Happy Coding! 🚀🐝