Pathfinding with A* Algorithm

Overview

This project implements the A* (A-star) pathfinding algorithm to find the shortest path between a start and goal point in a grid-based environment. The A* algorithm combines the benefits of Dijkstra's Algorithm and Greedy Best-First Search by using a heuristic function to optimize the search process.

Features

• Visual representation of the grid
• Interactive start and goal selection
• Obstacle placement
• Real-time pathfinding updates
• Adjustable grid size and heuristic function

How A* Works

A* uses the following cost function to determine the best path:

$$f(n) = g(n) + h(n)$$

where:

• g(n): The actual cost from the start node to node n
• h(n): The estimated cost from node n to the goal (heuristic function)

Usage

1. Clone the repository

git clone https://github.com/yourusername/pathfinding-a-star.git
cd pathfinding-a-star

2. Install dependencies (if applicable)

For Python projects:

pip install -r requirements.txt

3. Run the application

For Python:

python main.py

4. Interact with the UI to set the start and goal nodes and visualize the path.

Dependencies

Python:

• pygame
• numpy

Customization

• Modify the heuristic function in astar.py (for Python).
• Adjust grid size in the configuration file.
• Add different types of obstacles or weighted paths for advanced pathfinding.