Advanced SLAM in ROS2: Mapping with Cartographer

Linux, Nav2, ROS 2, Tutoriales

In this tutorial, you’ll learn how to use Google’s Cartographer with ROS2 to perform advanced 2D SLAM (Simultaneous Localization and Mapping). Cartographer is a real-time SLAM algorithm that provides loop closure and accurate map construction in dynamic environments. We’ll use a simulated TurtleBot3, but the steps are adaptable to real robots.

📝 Requirements

– ROS2 installed (e.g., Humble or Foxy)
– `cartographer_ros` installed and built in your workspace
– A robot simulation (e.g., TurtleBot3 in Gazebo)
– LIDAR sensor publishing on `/scan`
– TF tree properly set up between `base_link`, `odom`, and `laser`

Step 1: Launch Simulation and Cartographer

Start the robot simulation and the Cartographer SLAM launch file. Example with TurtleBot3:

ros2 launch turtlebot3_cartographer cartographer.launch.py use_sim_time:=true

🖥️Step 2: Move the Robot Around

Use keyboard teleoperation or predefined waypoints to guide the robot around the map:

ros2 run turtlebot3_teleop teleop_keyboard

Step 3: Save the Map

Once the robot has explored enough, save the generated map using map_server:

ros2 run nav2_map_server map_saver_cli -f ~/cartographer_map

🛠️ Passaggio 4: Risoluzione dei problemi

– Errori TF:

verificare che esistano i frame corretti (` base_link` , ` odom` , `laser`, ecc.) – i dati LIDAR non vengono visualizzati:

assicurati che `/scan` stia pubblicando e che il sensore funzioni – La mappa si sta spostando o è deformata:

controlla la messa a punto del modello di movimento nei parametri di Cartographer – Il file di avvio si blocca:

assicurati che Cartographer sia correttamente costruito e reperito nel tuo spazio di lavoro

Want to learn more?

You can find a detailed explaination of the autonomous navigation in the "Self Driving and ROS - Learn by Doing! Odometry and Control" course

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