Autonomous Room Mapping Robot

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Tech Stack

Technology	Usage	Proficiency
ROS2 Humble	Core robotics framework
Python	Node scripting and logic
Gazebo	Simulation and testing
RViz2	Visualization
SLAM Toolbox	Mapping and localization

A ROS2 Humble simulation project featuring autonomous room exploration with LIDAR-based SLAM and obstacle avoidance in Gazebo.

Features

• ✅ Autonomous navigation and exploration
• ✅ Real-time LIDAR-based mapping using SLAM Toolbox
• ✅ Intelligent obstacle avoidance
• ✅ Live visualization in RViz2
• ✅ Gazebo simulation environment

Prerequisites

• Ubuntu 22.04
• ROS2 Humble
• Gazebo
• Python 3

Installation

1. Install Dependencies

sudo apt update
sudo apt install -y ros-humble-gazebo-ros-pkgs ros-humble-cartographer \
ros-humble-cartographer-ros ros-humble-navigation2 ros-humble-nav2-bringup \
ros-humble-slam-toolbox ros-humble-turtlebot3-gazebo ros-humble-turtlebot3-msgs \
ros-humble-turtlebot3 python3-colcon-common-extensions

2. Set TurtleBot3 Model

echo "export TURTLEBOT3_MODEL=burger" >> ~/.bashrc
source ~/.bashrc

3. Clone and Build

mkdir -p ~/robot_mapping_ws/src
cd ~/robot_mapping_ws/src
git clone <your-repo-url> autonomous_mapper
cd ~/robot_mapping_ws
colcon build
source install/setup.bash

Usage

Launch the Complete System

source ~/robot_mapping_ws/install/setup.bash
ros2 launch autonomous_mapper mapping_launch.py

This single command starts:

• Gazebo simulation with TurtleBot3
• SLAM Toolbox for mapping
• RViz2 for visualization
• Autonomous explorer node

What You'll See

1. Gazebo Window: 3D simulation of the robot in the environment
2. RViz2 Window: Real-time map building and robot pose

Save the Map

Once satisfied with the mapping, save it:

ros2 run nav2_map_server map_saver_cli -f my_room_map

This creates:

• my_room_map.pgm - Map image
• my_room_map.yaml - Map metadata

How It Works

Autonomous Explorer Node

• Continuously reads LIDAR scan data
• Moves forward while safe
• Detects obstacles within 0.5m
• Intelligently rotates toward open space
• Adds random exploration variations

SLAM Toolbox

• Processes LIDAR data
• Builds occupancy grid map
• Localizes robot position
• Updates map in real-time

Obstacle Avoidance Algorithm

1. Monitor LIDAR 360° scan
2. Calculate minimum distance to obstacles
3. If distance < 0.5m: Avoid
   • Stop forward motion
   • Compare left vs right open space
   • Rotate toward larger opening
4. If distance > 0.5m: Explore
   • Move forward
   • Add random small turns for coverage

Customization

Adjust Robot Speed

Edit autonomous_mapper/autonomous_explorer.py:

self.linear_speed = 0.2  # m/s (increase for faster exploration)
self.angular_speed = 0.5  # rad/s (rotation speed)

Adjust Safety Distance

self.safe_distance = 0.5  # meters (obstacle detection threshold)

Change Gazebo World

Edit mapping_launch.py to use different worlds:

# Options: turtlebot3_world, turtlebot3_house, empty_world
'turtlebot3_world.launch.py'

Troubleshooting

Gazebo doesn't start

killall gzserver gzclient
source ~/.bashrc

Robot doesn't move

Check if explorer node is running:

ros2 node list
# Should show: /autonomous_explorer

No map in RViz2

1. Click "Add" button
2. Select "Map" display type
3. Set topic to /map

Package not found after build

source ~/robot_mapping_ws/install/setup.bash

Project Structure

autonomous_mapper/
├── autonomous_mapper/
│   ├── __init__.py
│   └── autonomous_explorer.py    # Main exploration logic
├── launch/
│   └── mapping_launch.py          # Launch file
├── resource/
│   └── autonomous_mapper          # Package marker
├── package.xml                    # Package dependencies
├── setup.py                       # Python package setup
└── README.md                      # This file

Future Enhancements

Development Progress

Feature	Progress
Autonomous Exploration
Obstacle Avoidance
SLAM Toolbox Integration
Frontier-based Exploration
Multi-Robot Coordination

• Frontier-based exploration
• Path planning integration
• Multi-robot coordination
• 3D mapping support
• Return to start position

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Author

AryanGanesh Kavuri