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Tutorial For Realsense-based Reconstruction

This tutorial demonstrates how to perform depth-camera based reconstruction using a realsense camera, NVIDIA VSLAM, and nvblox.

Note: This tutorial requires a compatible RealSense camera from the list available here.

Realsense Camera Firmware

This example is tested and compatible with realsense camera firmware version 5.13.0.50 which is available here.

Note: We experienced issues with the latest realsense firmware (version 5.14 at the time of publishing). It's possible at some point that this starts working, but our recommendation is to install exactly 5.13.0.50.

Host System Setup

We have found ROS 2 message delivery to be unreliable under high load without some small modifications to the QoS profile (especially on weaker machines). Before running this example run

sudo sysctl -w net.core.rmem_max=8388608 net.core.rmem_default=8388608

However this only sets these parameters until reboot. To set them permanently run:

echo -e "net.core.rmem_max=8388608\nnet.core.rmem_default=8388608\n" | sudo tee /etc/sysctl.d/60-cyclonedds.conf

More details on DDS tuning can be found here.

Installing the Dependencies

  1. Complete steps 1 and 2 described in the quickstart guide to set up your development environment and clone the required repositories.

  2. Stop git tracking the COLCON_IGNORE file in the realsense_splitter package and remove it.

    cd ${ISAAC_ROS_WS}/src/isaac_ros_nvblox/nvblox_examples/realsense_splitter && \
  git update-index --assume-unchanged COLCON_IGNORE && \
  rm COLCON_IGNORE

Note: The COLCON_IGNORE file was added to remove the dependency to realsense-ros for users that do not want to run the RealSense examples.

  1. Complete the realsense setup tutorial to set up librealsense outside of the isaac_ros_common docker, clone realsense_ros, and to configure the container for use with realsense.

  2. Download the code for Isaac ROS Visual SLAM and Isaac ROS NITROS.

    cd ${ISAAC_ROS_WS}/src && \
  git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_visual_slam.git && \
  git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_nitros.git

  3. Launch the Docker container using the run_dev.sh script (ISAAC_ROS_WS environment variable will take care of the correct path depending upon SD card or SSD setup as mentioned here):

    Note: This step requires access to the internet to be able to build and launch the Docker container properly!

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
  ./scripts/run_dev.sh ${ISAAC_ROS_WS}

  4. Inside the container, install package-specific dependencies via rosdep:

    cd /workspaces/isaac_ros-dev/ && \
  rosdep install -i -r --from-paths src --rosdistro humble -y --skip-keys "libopencv-dev libopencv-contrib-dev libopencv-imgproc-dev python-opencv python3-opencv nvblox"

  5. Build and source the workspace:

    cd /workspaces/isaac_ros-dev && \
  colcon build --symlink-install && \
  source install/setup.bash

Example with Realsense Live Data

  1. Complete the sections above.

  2. Connect the RealSense device to your machine.

  3. At this point, verify that the RealSense camera device is properly connected and streaming by running realsense-viewer as mentioned here:

    realsense-viewer

  4. If successful, exit realsense-viewer and run the launch file to spin up the example:

    ros2 launch nvblox_examples_bringup realsense_example.launch.py

Here is a few seconds of the result from running the example:

Example with Realsense Recorded Data

If you want to run the realsense example on recorded data refer to the realsense recording tutorial.

Troubleshooting

See our troubleshooting page here.