A* Pathfinding Visualizer 🔍🧭

This repository contains an implementation of the A* (A-Star) pathfinding algorithm in Python, using a visual maze environment. It simulates node expansion and optimal path search using both Manhattan and Euclidean heuristics.

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🚀 Features

• A* algorithm implementation from scratch
• Maze generation and visualization
• Option to toggle between Manhattan and Euclidean distances
• Visualization of search process and final path

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🧠 Algorithms

• A Search*: Uses cost function f(n) = g(n) + h(n) to explore the shortest path.
• Heuristics:
  • Manhattan Distance
  • Euclidean Distance

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📁 Files

• astar.py – Main script with the search algorithm.
• maze_2.py – Maze environment for testing the algorithm.
• README.md – Documentation and guide.

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📸 Demo

A GIF or image of your maze and path would be perfect here once available.

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⚙️ Requirements

• Python 3.x
• matplotlib and numpy

Install dependencies:

pip install numpy matplotlib

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🧪 How to Run

Clone the repository:

git clone https://github.com/yourusername/AStar-Pathfinding-Visualizer.git
cd AStar-Pathfinding-Visualizer

Make sure maze_2.py is in the same directory.

Run the script:

python astar.py

To toggle between different maps:

m = Maze(map_num=1)  # Change 1 to 2 to use a different map

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✍️ Author

Ashok Kumar Meena BTech, Electrical Engineering IIT Madras | Firmware Developer @ Ather Energy GitHub: github.com/yourusername

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📜 License

MIT License.