FastMapping Algorithm#

FastMapping application is the Intel® optimized version of octomap.

For more information on FastMapping, see how_it_works.

Source Code#

The source code of this component can be found here: FastMapping

Prerequisites#

Complete the get started guide before continuing.

Run the FastMapping Standalone Application#

  1. To download and install the FastMapping standalone sample application run the command below:

    sudo apt-get install ros-jazzy-fast-mapping

    sudo apt-get install ros-humble-fast-mapping

    Note:

    The ros-jazzy-fast-mapping package includes a ROS 2 bag, which will be used for this tutorial. After the installation, the ROS 2 bag can be found at /opt/ros/jazzy/share/bagfiles/spinning/. ros-humble-fast-mapping can be found at similar directory path.

  2. Set up your ROS 2 environment

    source /opt/ros/jazzy/setup.bash

    source /opt/ros/humble/setup.bash

  3. Run the FastMapping sample application using a ROS 2 bag of a robot spinning:

    ros2 launch fast_mapping fast_mapping.launch.py

    Expected output:

    open-edge-platform/edge-ai-suites

  4. Run the FastMapping sample application using Intel® RealSense™ camera input with RTAB-Map:

    ros2 launch fast_mapping fast_mapping_rtabmap.launch.py

Once the tutorial is launched, the input from the Intel® RealSense™ camera is used and a 3D voxel map of the environment can be viewed in rviz.

To close this application, type Ctrl-c in the terminal where you ran the launch script.

Troubleshooting#

For general robot issues, refer to Troubleshooting.