# Enable 2D lidar SLAM with `cartographer_ros` The 2D lidar SLAM sample application is based on `Cartographer`, which is capable of completing indoor map construction and localization based on 2D lidar sensors. It's suitable for indoor navigation of robots. ![2D lidar SLAM](data:image/png;base64,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) ## Pipeline flow for 2D lidar SLAM
Cartographer
ROS node
Cartographer occupancy grid node
2D lidar SLAM
/scan_matched
_points2
/tracked
_pose
/tf
/map
2D lidar
(/scan)
Robot base
(/odom)
QRB ROS SLAM client
(/qrb_ros_slam)
Submap list
Internal module
ROS node
Topic
External module
## ROS nodes used in the 2D lidar SLAM pipeline | ROS node | Description | | --- | --- | | `cartographer_node` | Receives `/scan` and `/odom` topics, executes mapping, localization, and saves the map or queries the relocation status. The node is based on the ROS service `qrb_slam_command`. | | `cartographer_occupancy_grid_node` | Receives map-related topics sent by the `cartographer_node` and publishes a ROS standard map (`/static_map`). | ## ROS topics/services used in 2D lidar SLAM | ROS topic | Type | Published by | | --- | --- | --- | | `/tracked_pose` | `geometry_msgs.msg.PoseStamped` | `cartographer_node` | | `/tf` | `tf2_msgs.msg.TFMessage` | `cartographer_node` | | `/submap_list` | `cartographer_ros_msgs.msg.SubmapList` | `cartographer_node` | | `/scan_matched_points2` | `sensor_msgs.msg.PointCloud2` | `cartographer_node` | | `/map` | `nav_msgs.msg.OccupancyGrid` | `cartographer_occupancy_grid_node` | | ROS service | Type | Provided by | | --- | --- | --- | | `/qrb_slam_command` | `qrb_ros_slam_msgs.srv.SlamCommand` | `cartographer_node` | ## Prerequisites You have completed the following settings in [Set up the environment for running sample applications](https://docs.qualcomm.com/doc/80-70030-265/topic/quick_start.html#setup-demo-qs) (Skip the settings of **Set up host docker**). - Set up the device - Set up the host computer ## Run out-of-the-box 2D lidar SLAM **Steps** 1. Set up the robot base. Note The following configuration applies exclusively to Qualcomm’s robot base. If you are using a custom or third-party robot base, skip this configuration step and apply configurations appropriate to your own robot base. 1. Open a new terminal connect to the device. source /usr/share/qirp-setup.sh export ROS_DOMAIN_ID=124 Copy to clipboard 2. Select the robot base model. > > > - 0604 AMR: `robot_base` (default) > - Mini AMR: `robot_base_mini` export ROBOT_BASE_MODEL=robot_base_mini Copy to clipboard 3. (Optional) If you don't connect the ultrasonic sensor to the MCB, disable ultrasound emergency stop. mount -o remount rw, /usr vi /usr/share/qrb_ros_robot_base/config/[robot base model file] # modify ultra_enable: false Copy to clipboard 4. Launch the robot base AMR. ros2 launch qrb_ros_robot_base robot_base.launch.py Copy to clipboard 2. Set up the 2D lidar in a new terminal. > > > source /usr/share/qirp-setup.sh > export ROS_DOMAIN_ID=124 > export HOME=/data > ros2 launch rplidar_ros rplidar_a3_launch.py > Copy to clipboard 3. Run the 2D lidar SLAM in a new terminal. source /usr/share/qirp-setup.sh export ROS_DOMAIN_ID=124 mount -o remount rw, /usr ros2 launch cartographer_ros qrb_2d_lidar_slam.launch.py Copy to clipboard 4. Run the `qrb_slam_service_request` script in a new terminal. ssh root@[IP address] source /usr/share/qirp-setup.sh export ROS_DOMAIN_ID=124 chmod 777 /usr/share/cartographer_ros/scripts/qrb_slam_service_request.sh bash /usr/share/cartographer_ros/scripts/qrb_slam_service_request.sh Copy to clipboard 5. Use the keyboard to send control commands, such as start mapping. ![../../../../_images/2d-slam-keyboard-cmds.png](data:image/png;base64,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) Last Published: Jul 23, 2026 [Previous Topic Control AMR in the simulator with simulation\_sample\_amr\_simple\_motion](https://docs.qualcomm.com/bundle/publicresource/80-70030-265/topics/simulation_sample_amr_simple_motion.md) [Next Topic Enable people tracking with follow\_me](https://docs.qualcomm.com/bundle/publicresource/80-70030-265/topics/followme.md)