Robot Localization

This project implements a robot localization algorithm that leverages Bayesian updates to estimate the robot's position in a 2D grid environment. It's designed for educational purposes and can be applied to robotic navigation in uncertain environments.

How it Works

• Robot Localization: Uses Bayesian updates to estimate the robot's position on a 2D grid.
• Sensor Model: Simulates noisy sensor data to mimic real-world conditions and adjusts probabilities accordingly.
• Motion Model: Predicts the robot's new state and updates the probability distribution when the robot moves.
• Visualization: Real-time 3D plot of the probability distribution using matplotlib.

Features

• 2D grid-based environment
• Bayesian probability updates
• Real-time 3D visualization of probability distribution
• SFML-based GUI

Demo

Prerequisites

• C++
• CMake 3.10+
• SFML 2.5+
• Python 3.8+
• matplotlib
• numpy
• scipy

Installation

Install Dependencies

# Ubuntu/Debian
sudo apt-get update
sudo apt-get install cmake libsfml-dev python3-dev python3-numpy python3-matplotlib python3-scipy

Build from Source

# Clone repository
git clone https://github.com/YOUR_USERNAME/robot-localization.git
cd robot-localization

# Build
chmod +x [build.sh](http://_vscodecontentref_/1)
[build.sh](http://_vscodecontentref_/2)

# Run
cd build
./robot_simulator

System-wide Installation (optional)

cd build
sudo make install

Usage

# Run the simulator
./build/robot_simulator