Installation

Note

We provide docker images so that the user can do calibration without installation: Docker images

Warn

On Ubuntu 20.04, install a newer cmake.

Dependencies

• ROS1/ROS2
• PCL
• OpenCV
• GTSAM
• Ceres
• Iridescence
• SuperGlue [optional]

Install Common dependencies

# Install dependencies
sudo apt install libomp-dev libboost-all-dev libglm-dev libglfw3-dev libpng-dev libjpeg-dev

# Install GTSAM
git clone https://github.com/borglab/gtsam
cd gtsam && git checkout 4.2a9
mkdir build && cd build
# For Ubuntu 22.04, add -DGTSAM_USE_SYSTEM_EIGEN=ON
cmake .. -DGTSAM_BUILD_EXAMPLES_ALWAYS=OFF \
         -DGTSAM_BUILD_TESTS=OFF \
         -DGTSAM_WITH_TBB=OFF \
         -DGTSAM_BUILD_WITH_MARCH_NATIVE=OFF
make -j$(nproc)
sudo make install

# Install Ceres
git clone --recurse-submodules https://github.com/ceres-solver/ceres-solver
cd ceres-solver
git checkout e47a42c2957951c9fafcca9995d9927e15557069
mkdir build && cd build
cmake .. -DBUILD_EXAMPLES=OFF -DBUILD_TESTING=OFF -DUSE_CUDA=OFF
make -j$(nproc)
sudo make install

# Install Iridescence for visualization
git clone https://github.com/koide3/iridescence --recursive
mkdir iridescence/build && cd iridescence/build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)
sudo make install

Install SuperGlue (Optional)

Warning

SuperGlue is not allowed to be used for commercial purposes. You must carefully check and follow its licensing conditions.

pip3 install numpy opencv-python torch matplotlib
git clone https://github.com/magicleap/SuperGluePretrainedNetwork.git

echo 'export PYTHONPATH=$PYTHONPATH:/path/to/SuperGluePretrainedNetwork' >> ~/.bashrc
source ~/.bashrc

Build direct_visual_lidar_calibration

# ROS1
cd ~/catkin_ws/src
git clone https://github.com/koide3/direct_visual_lidar_calibration.git --recursive
cd .. && catkin_make

# ROS2
cd ~/ros2_ws/src
git clone https://github.com/koide3/direct_visual_lidar_calibration.git --recursive
cd .. && colcon build