https://github.com/erroujioussama/astar-and-dijkstra-based-path-planners

MATLAB implementations for Dijkstra's algorithm and A* algorithm used in grid-based path planning
https://github.com/erroujioussama/astar-and-dijkstra-based-path-planners

matlab motion-planning robotics

Last synced: 3 months ago
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MATLAB implementations for Dijkstra's algorithm and A* algorithm used in grid-based path planning

• Host: GitHub
• URL: https://github.com/erroujioussama/astar-and-dijkstra-based-path-planners
• Owner: ErroujiOussama
• License: mit
• Created: 2024-07-29T00:41:04.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-29T13:25:19.000Z (6 months ago)
• Last Synced: 2024-10-04T21:44:57.574Z (3 months ago)
• Topics: matlab, motion-planning, robotics
• Language: MATLAB
• Homepage:
• Size: 12.7 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# A* & Dijkstra-based Path Planners

This repository contains MATLAB implementations of path planning algorithms based on Dijkstra's algorithm and A* algorithm for grid-based environments.

### Dijkstra's Algorithm

Dijkstra's algorithm finds the shortest path between nodes in a weighted graph by iteratively selecting the node with the smallest known distance, updating its neighbors' distances, and marking it as visited. It ensures the shortest path in graphs with non-negative

    weights.

### A* Algorithm

The A* algorithm enhances Dijkstra's by using heuristics to prioritize paths. It combines the actual cost to a node with an estimated cost to the goal, speeding up the search for the shortest path, especially in large graphs or grids.

## Contents

- **AStarGrid.m**: Implementation of the A* algorithm for grid-based pathfinding.

- **DijkstraGrid.m**: Implementation of Dijkstra's algorithm for grid-based pathfinding.

- **run.m**: Script to run and test the path planning algorithms.

## Features

- Path planning in grid-based environments

- Visualization of the pathfinding process

- Customizable start and goal positions

## Usage

- Run the script:

    ```sh

    run.m

    ```