Autonomous TurtleBot3 Navigation in Maze Environment

This repository contains a ROS2-based simulation for multi-robot navigation in a maze environment using TurtleBot3 robots. The project includes mapping, navigation, and synchronous robot behavior triggered by external signals.

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Project Overview

This project aims to simulate and implement the following functionalities:

1. SLAM (Simultaneous Localization and Mapping): Creating a 2D map of the maze environment.
2. Multi-Robot Navigation: Enabling multiple robots to navigate to target positions in the maze.
3. Synchronous Behavior: Robots start moving simultaneously to new rooms upon receiving a specific signal.
4. Simulation Environment: Built using Gazebo with TurtleBot3 robots and a custom maze world.

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Folder Structure

autonomous_tb3/
├── autonomous_tb3/
│   ├── __init__.py
│   ├── goal.py              # Script for multi-robot goal publishing
│   ├── maze_solver.py       # Solver for maze navigation (if implemented)
│   ├── send_goals.py        # Custom script to send goals to robots
├── config/                  # Configuration files for SLAM, navigation, and RViz
├── launch/                  # Launch files for SLAM, navigation, and robot spawning
│   ├── centralized_slam.launch.py
│   ├── empty_world_no_robot.launch.py
│   ├── multi_mapping.launch.py
│   ├── multi_robot_navigation.launch.py
│   ├── new_navigation.launch.py
│   ├── slam_toolbox.launch.py
├── maps/                    # Contains YAML and PGM map files
├── models/                  # Custom models for the maze and robots
├── urdf/                    # TurtleBot3 URDF and xacro files
├── world/                   # Gazebo world files for the maze environment
├── worlds/                  # multi_maze world that we created
├── rviz2_multi.rviz         # RViz configuration file for multi-robot navigation
├── package.xml              # ROS2 package configuration
├── setup.cfg                # Python setup configuration
├── setup.py                 # Python setup script

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How to Use

1. Clone the Repository

git clone https://github.com/yourusername/autonomous_tb3.git
cd autonomous_tb3

2. Build the Workspace

Ensure you have a ROS2 workspace set up. Place this repository in the src folder and build the workspace:

colcon build --symlink-install
source install/setup.bash

3. Run SLAM for Mapping

To create a map of the maze environment:

ros2 launch autonomous_tb3 slam_toolbox.launch.py

4. Save the Map

After completing the mapping in RViz:

ros2 run nav2_map_server map_saver_cli -f ~/map

5. Run Multi-Robot Navigation

To start navigation with multiple robots:

ros2 launch autonomous_tb3 multi_robot_navigation.launch.py

6. Trigger Synchronous Movement

Run the custom script to send goals to the robots:

ros2 run autonomous_tb3 goal

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Features

• Gazebo Simulation: Simulates a real-world maze environment.
• Multi-Robot Coordination: Allows multiple robots to navigate simultaneously.
• SLAM Integration: Uses slam_toolbox for mapping.
• Navigation Stack: Leverages ROS2 Navigation Stack for planning and execution.
• Custom Goal Management: Includes a script to dynamically publish goals.

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Future Enhancements

1. Implement real-world testing with hardware.
2. Improve robot behavior for obstacle avoidance in narrow spaces.
3. Add support for advanced communication protocols between robots.

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Simulation Snapshots

World in Gazebo

Generated Map

RViz Visualization

Real Setup

Acknowledgments

This project uses:

• TurtleBot3 Simulation
• Gazebo
• ROS2 Navigation