Installation

Using the Docker Images

1. Clone and build the docker image
   

First make sure that you have install docker on your system using the official Docker Get Docker guide. We can then clone and build the docker container using:

git clone https://github.com/ethz-asl/kalibr.git
cd kalibr
docker build -t kalibr -f Dockerfile_ros1_20_04 . # change this to whatever ubuntu version you want

2. Mounting a data folder for use in the container
   

We can now mount the data folder in the container /data path and enter the command prompt. Some more details can be found on the ROS wiki for Docker.

FOLDER=/path/to/your/data/on/host
xhost +local:root
docker run -it -e "DISPLAY" -e "QT_X11_NO_MITSHM=1" \
    -v "/tmp/.X11-unix:/tmp/.X11-unix:rw" \
    -v "$FOLDER:/data" kalibr

3. Inside the docker, running commands
   

Using the above command you should have entered the docker container bash prompt. From here you should be able to run kalibr on any files that are in your /data directory. You will want to first load your ROS environment variables.

source devel/setup.bash
rosrun kalibr kalibr_calibrate_cameras \
    --bag /data/cam_april.bag --target /data/april_6x6.yaml \
    --models pinhole-radtan pinhole-radtan \
    --topics /cam0/image_raw /cam1/image_raw

Building Kalibr from Source

The codebase is built on top of the Robot Operating System (ROS) and has been tested building on Ubuntu 16.04, 18.04, 20.04 systems with ROS Kinetic, Melodic, and Noetic. We also recommend installing the catkin_tools build for easy ROS building. More information on building with catkin and ROS can be found here. Please see the official instructions to install ROS:

• Ubuntu 16.04 ROS 1 Kinetic (uses OpenCV 3.3)
• Ubuntu 18.04 ROS 1 Melodic (uses OpenCV 3.2)
• Ubuntu 20.04 ROS 1 Noetic (uses OpenCV 4.2)

1. Install ROS 1 on your system
   

Here are some example commands that will install both the ROS 1 desktop environment and catkin tools.

sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
sudo apt-get update
export ROS1_DISTRO=noetic # kinetic=16.04, melodic=18.04, noetic=20.04
sudo apt-get install ros-$ROS1_DISTRO-desktop-full
sudo apt-get install python-catkin-tools # ubuntu 16.04, 18.04
sudo apt-get install python3-catkin-tools python3-osrf-pycommon # ubuntu 20.04

2. Install the build and run dependencies
   

The general requirements common to all version of Ubuntu are the following:

sudo apt-get install -y \
    git wget autoconf automake nano \
    libeigen3-dev libboost-all-dev libsuitesparse-dev \
    doxygen libopencv-dev \
    libpoco-dev libtbb-dev libblas-dev liblapack-dev libv4l-dev

Then due to different Python versions, you will need to install the following:

# Ubuntu 16.04
sudo apt-get install -y python2.7-dev python-pip python-scipy \
    python-matplotlib ipython python-wxgtk3.0 python-tk python-igraph python-pyx
# Ubuntu 18.04
sudo apt-get install -y python3-dev python-pip python-scipy \
    python-matplotlib ipython python-wxgtk4.0 python-tk python-igraph python-pyx
# Ubuntu 20.04
sudo apt-get install -y python3-dev python3-pip python3-scipy \
    python3-matplotlib ipython3 python3-wxgtk4.0 python3-tk python3-igraph python3-pyx

3. Create a catkin workspace and clone the project
   

First we can create a workspace. It is important to configure this to build in release mode otherwise optimization will be slow.

mkdir -p ~/kalibr_workspace/src
cd ~/kalibr_workspace
export ROS1_DISTRO=noetic # kinetic=16.04, melodic=18.04, noetic=20.04
source /opt/ros/$ROS1_DISTRO/setup.bash
catkin init
catkin config --extend /opt/ros/$ROS1_DISTRO
catkin config --merge-devel # Necessary for catkin_tools >= 0.4.
catkin config --cmake-args -DCMAKE_BUILD_TYPE=Release

We can then clone the project:

cd ~/kalibr_workspace/src
git clone https://github.com/ethz-asl/kalibr.git

4. Build the code using the Release configuration. Depending on the available memory, you might need to reduce the build threads (e.g. add -j2 to catkin_make)
   

cd ~/kalibr_workspace/
catkin build -DCMAKE_BUILD_TYPE=Release -j4

5. Once the build is finished you have to source the catkin workspace setup to use Kalibr

source ~/kalibr_workspace/devel/setup.bash
rosrun kalibr <command_you_want_to_run_here>

References

Please cite the appropriate papers when using this library or parts of it in an academic publication.

1. L. Oth, P. Furgale, L. Kneip, R. Siegwart (2013). Rolling Shutter Camera Calibration, In Proc. of the IEEE Computer Vision and Pattern Recognition (CVPR)
2. J. Maye, P. Furgale, R. Siegwart (2013). Self-supervised Calibration for Robotic Systems, In Proc. of the IEEE Intelligent Vehicles Symposium (IVS)
3. Paul Furgale, T D Barfoot, G Sibley (2012). Continuous-Time Batch Estimation Using Temporal Basis Functions. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2088–2095, St. Paul, MN.
4. Paul Furgale, Joern Rehder, Roland Siegwart (2013). Unified Temporal and Spatial Calibration for Multi-Sensor Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan.
5. Joern Rehder, Janosch Nikolic, Thomas Schneider, Timo Hinzmann, Roland Siegwart (2016). Extending kalibr: Calibrating the extrinsics of multiple IMUs and of individual axes. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4304-4311, Stockholm, Sweden.