lbr_fri_ros2_stack

ROS 2 packages for the KUKA LBR, including communication to the real robot via the Fast Robot Interface (FRI) and Gazebo simulation support. Included are the iiwa7, iiwa14, med7, and med14.

LBR IIWA7 R800	LBR IIWA14 R820	LBR Med7 R800	LBR Med14 R820

Documentation

Full documentation available here.

Quick Start

1. Install ROS 2 development tools

   sudo apt install ros-dev-tools

2. Create a workspace, clone, and install dependencies

   mkdir -p lbr-stack/src && cd lbr-stack
   vcs import src --input https://raw.githubusercontent.com/lbr-stack/lbr_fri_ros2_stack/humble/lbr_fri_ros2_stack/repos.yaml
   rosdep install --from-paths src -i -r -y

3. Build

   colcon build --symlink-install --cmake-args -DFRI_CLIENT_VERSION=1.15 --no-warn-unused-cli # replace by your FRI client version

Note

FRI client is added as external CMake project via fri_vendor and must be available as branch, refer README.

4. Launch the simulation via

   source install/setup.bash
   ros2 launch lbr_bringup bringup.launch.py \
       model:=iiwa7 # [iiwa7, iiwa14, med7, med14] \
       sim:=true # [true, false] \
       rviz:=true # [true, false] \
       moveit:=true # [true, false]

Tip

List all arguments for the launch file via ros2 launch lbr_bringup bringup.launch.py -s

Now, run the demos. To get started with the real robot, checkout the Documentation above.

Citation

If you enjoyed using this repository for your work, we would really appreciate ❤️ if you could cite it, as it helps us to continue offering support.

@misc{huber2023lbrstack,
      title={LBR-Stack: ROS 2 and Python Integration of KUKA FRI for Med and IIWA Robots}, 
      author={Martin Huber and Christopher E. Mower and Sebastien Ourselin and Tom Vercauteren and Christos Bergeles},
      year={2023},
      eprint={2311.12709},
      archivePrefix={arXiv},
      primaryClass={cs.RO}
}

Acknowledgements

This work was supported by core and project funding from the Wellcome/EPSRC [WT203148/Z/16/Z; NS/A000049/1; WT101957; NS/A000027/1].

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101016985 (FAROS project).