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5.4.1 SLAM Mapping

Overview​

SLAM stands for Simultaneous Localization and Mapping. This section uses ROS2 SLAM-Toolbox as the mapping algorithm. Control the robot in Gazebo to build a map and observe the mapping result in Rviz2. SLAM-Toolbox runs on the RDK, while Gazebo and Rviz2 run on a PC on the same network as the RDK.

Supported Platforms​

PlatformRuntime Environment
RDK X3, RDK X3 Module,Ubuntu 20.04 (Foxy), Ubuntu 22.04 (Humble)
RDK X5, RDK X5 ModuleUbuntu 22.04 (Humble)
RDK S100, RDK S100PUbuntu 22.04 (Humble)
RDK S600Ubuntu 24.04 (Jazzy)

Preparation​

RDK Platform​

  1. The RDK has been flashed with the Ubuntu system image.

  2. TogetheROS.Bot has been successfully installed on the RDK.

  3. After tros.b is installed, install SLAM-Toolbox

# 配置tros.b环境
source /opt/tros/setup.bash
sudo apt-get install ros-${ROS_DISTRO}-slam-toolbox
info

If installation fails with the following error:

  The following packages have unmet dependencies:
   ros-foxy-slam-toolbox : Depends: ros-foxy-nav2-map-server but it is not going to be installed
  E: Unable to correct problems, you have held broken packages.

Run the following commands before installing again:

apt update

sudo apt install libwebp6=0.6.1-2ubuntu0.20.04.3

Note

If the sudo apt update command fails or reports an error, please refer to the FAQ section Q10: How to handle apt update command failure or error? for resolution.

Note

If the sudo apt update command fails or reports an error, please refer to the FAQ section Q6: How to handle apt update command failure or error? for resolution.

:::

  1. A PC on the same network as the RDK with Ubuntu, ROS2 desktop edition, Gazebo simulation environment, and Rviz2 visualization tool installed.
source /opt/ros/foxy/setup.bash

Ubuntu 20.04 and ROS2 Foxy desktop edition

After ROS2 is installed on the PC, install Gazebo and Turtlebot3 related packages as follows:

sudo apt-get install ros-${ROS_DISTRO}-gazebo-*
sudo apt install ros-${ROS_DISTRO}-turtlebot3
sudo apt install ros-${ROS_DISTRO}-turtlebot3-bringup
sudo apt install ros-${ROS_DISTRO}-turtlebot3-simulations
sudo apt install ros-${ROS_DISTRO}-teleop-twist-keyboard

Usage​

RDK Platform​

This section describes how to run the SLAM algorithm on the RDK and observe the mapping result on the PC.

Start the simulation environment on the PC:

source /opt/ros/foxy/setup.bash
export TURTLEBOT3_MODEL=burger
ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py
info

If startup fails with the error [ERROR] [gzclient-2]: process has died, run source /usr/share/gazebo/setup.sh and start again.

The simulation environment is shown below:

Open another console on the PC and start Rviz2 to observe the mapping result:

source /opt/ros/foxy/setup.bash
ros2 launch turtlebot3_bringup rviz2.launch.py

After opening Rviz2, add the "map" visualization option to display the built map as shown below:

Run SLAM-Toolbox on the RDK:

# 配置tros.b环境
source /opt/tros/setup.bash
#启动SLAM launch文件
ros2 launch slam_toolbox online_sync_launch.py

Open another console on the PC and start the control tool. Use the keyboard to control robot movement. Refer to the log printed in the console for control instructions, which are not repeated here:

source /opt/ros/foxy/setup.bash
ros2 run teleop_twist_keyboard teleop_twist_keyboard

Drive the robot around. As the lidar detects more environmental information, the SLAM algorithm builds the environment map, which can be observed in Rviz2.

Result Analysis​

The RDK terminal outputs the following information:

[INFO] [launch]: All log files can be found below /root/.ros/log/2022-06-10-06-40-34-204213-ubuntu-5390
[INFO] [launch]: Default logging verbosity is set to INFO
[INFO] [sync_slam_toolbox_node-1]: process started with pid [5392]
[sync_slam_toolbox_node-1] [INFO] [1654843239.403931058] [slam_toolbox]: Node using stack size 40000000
[sync_slam_toolbox_node-1] [INFO] [1654843240.092340814] [slam_toolbox]: Using solver plugin solver_plugins::CeresSolver
[sync_slam_toolbox_node-1] [INFO] [1654843240.096554433] [slam_toolbox]: CeresSolver: Using SCHUR_JACOBI preconditioner.
[sync_slam_toolbox_node-1] Info: clipped range threshold to be within minimum and maximum range!
[sync_slam_toolbox_node-1] [WARN] [1654843589.431524393] [slam_toolbox]: maximum laser range setting (20.0 m) exceeds the capabilities of the used Lidar (3.5 m)
[sync_slam_toolbox_node-1] Registering sensor: [Custom Described Lidar]
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