A* Path Planning Algorithm

A Python implementation of the Search algorithm for path planning in a grid-based environment. This project allows you to find the optimal path from a starting point to a goal point while avoiding obstacles.

Table of Contents

• Introduction
• Features
• Getting Started
  • Prerequisites
  • Installation
• Usage
  • Configuring Parameters
• Results
• Contributing
• License

Introduction

Path planning is a fundamental problem in robotics and autonomous systems.

Features

• Depth First search algorithm implementation.
• Breadth First search algorithm implementation.
• A* search algorithm implementation.
• Uniform Cost Search algorithm implementation.
• Customizable motion type (4n or 8n) for path generation.
• Choice of heuristic calculation (manhattan or euclidean) for estimating costs.
• Dynamic obstacle support for real-world simulations.
• Memory and execution time measurement.
• Interactive visualization of the path planning process using Matplotlib.

Getting Started

Prerequisites

• Python 3.x
• Matplotlib (for visualization)
• NumPy (for array manipulation)
• pandas (for reading configuration data)
• (Optional) tracemalloc (for memory tracking)

Installation

. Clone the repository:

git clone https://github.com/yourusername/path-planning.git  -- pip install matplotlib numpy pandas tracemalloc