If you prefer, you can skip the steps below and use the Docker image instead.
OpenCV 3.2, which is what ships with Ubuntu 18.04, has a buggy ArUco pose detection implementation. The instructions
below assume you have OpenCV 3.4 installed in /usr/local/. OpenCV 3.4 can be easily installed as follows:
git clone https://github.com/RoboticsYY/opencv_deb_install.git
sudo dpkg -i opencv_deb_install/OpenCV-3.4/OpenCV-3.4.5-x86_64-*
If you haven't already, install catkin:
sudo apt install ros-melodic-catkin python-catkin-tools
The simulation also requires Gazebo:
sudo apt install ros-melodic-gazebo-ros ros-melodic-gazebo-plugins ros-melodic-gazebo-ros-control \
ros-melodic-joint-state-controller ros-melodic-position-controllers ros-melodic-joint-trajectory-controller
Set up a new workspace using the included moveit_cal_simulation.rosinstall:
mkdir -p ~/ws_moveit_cal/src
cd ~/ws_moveit_cal/src
wstool init .
wstool merge -t . https://raw.githubusercontent.com/JStech/moveit_cal_simulation/main/moveit_cal_simulation.rosinstall
wstool update -t .
rosdep install -y --from-paths . --ignore-src --rosdistro melodic
Configure and build:
cd ~/ws_moveit_cal
catkin config --extend /opt/ros/melodic --cmake-args -DOpenCV_DIR=/usr/local/share/OpenCV -DCMAKE_BUILD_TYPE=Release
catkin build
roslaunch panda_moveit_config demo_gazebo.launch
From there, follow the tutorial.