Differential Drive Robot with SLAM and Autonomous Navigation

This project implements a differential drive robot equipped with SLAM (Simultaneous Localization and Mapping) capabilities using gmapping. The robot creates a 2D map of its environment and saves it locally, which can then be used for localization through AMCL (Adaptive Monte Carlo Localization) and autonomous navigation using move_base.

Table of Contents

• Project Overview
• Features
• Installation
• Usage
• Images
• Contributing

Project Overview

The differential drive robot in this project performs:

• Mapping: Uses gmapping to generate a 2D map of its environment.
• Localization: Uses the generated map with AMCL for localization.
• Navigation: Plans and follows paths using move_base to autonomously navigate the environment.

This project is designed for use in various indoor environments such as warehouses, greenhouses, or industrial settings, where autonomous mapping and navigation are essential.

Features

• Gmapping for SLAM: Creates a real-time map of the environment.
• AMCL Localization: Localizes the robot on a pre-existing map.
• Move Base Navigation: Autonomously navigates to specified goals using path planning.
• Real-time Visualization: Visualizes the robot, map, and path using Rviz.

Installation

Prerequisites

Ensure the following dependencies are installed:

• ROS Noetic
• gmapping package:

  sudo apt-get install ros-noetic-slam-gmapping
  

• amcl package:

  sudo apt-get install ros-noetic-amcl
  sudo apt-get install ros-noetic-dwa-local-planner
  

• move_base package:

  sudo apt-get install ros-noetic-move-base
  

• teleop-twis-keyboard package:

  sudo apt-get install ros-noetic-teleop-twist-keyboard
  

• map-server package:

  sudo apt-get install ros-noetic-map-server
  

Steps

1. Clone the repository:

   git clone https://github.com/S-Sidharthan/ROS-slam-amcl-autonomous-robot.git
   

2. Build the project:

   cd ROS-slam-amcl-autonomous-robot
   catkin_make
   

3. Source the workspace:

   source devel/setup.bash
   

Usage

Mapping

To start mapping the environment, run:

roslaunch robot_gazebo robot_gazebo.launch
roslaunch yourproject gmapping.launch
rosrun teleop_twist_keyboard teleop_twist_keyboard.py

Localization and Navigation

To localize and navigate using the saved map : (Note: change the map path in amcl.launch)

roslaunch diff_wheeled_robot amcl.launch 

Images

Figure 1: Environment mapping.

Figure 2: Robot navigating through the mapped environment using move_base.

Video Demo

Watch a demo of the robot in action on YouTube:

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests for improvements.