rem

rem (Ros Environment Manager) is a tool based on Docker, which allows you to easily manage multiple versions of ROS environments and brings you the same coding experience as on your local machine.

feature

• Xorg image forwarding and GPU acceleration.
• Same configuration and softwares between host machine and the virtual ROS environment. No need to rebuild the image locally.
• Easily integrates with VSCode DevContainer.
• Easily configure project dependencies in the environment.

Installation

rem depends on Python and Docker. You can install rem via pip with the following command:

pip install -r requirements.txt
pip install -e .

Configure the terminal to automatically source the ROS environment, supports both bash and zsh.

rem init

Usage

rem's syntax is similar to Docker's but with some encapsulation. You can view all commands by running rem -h.

For instance, if you want to obtain a ROS Noetic environment, you first need to pull a remote image with rem pull noetic, or build a local image with rem build noetic.

Next, create and start the container by running rem run noetic.

Finally, enter the container for development by using rem attach noetic or rem exec noetic.

You can replace "noetic" with any other supported ROS version of your choice. And by adding your project configuration in config.json, dependencies will be automatically installed when building the image locally.

To integrate with VSCode, you need to install the DevContainer plugin and configure in VSCode.

"terminal.integrated.defaultProfile.linux": "zsh_rem",
"terminal.integrated.profiles.linux": {
    "zsh_rem": {
        "path": "/exec.sh"
    }
}

Known limitations

• Currently does not support AMD GPU acceleration
• Due to the difference in Ubuntu's password encryption algorithm, it is necessary to manually enter the user password on Kinetic and Melodic
• If there is a significant discrepancy between the host machine's operating system and the ROS environment's operating system, there may be some configurations is not universally applicable.
• Ubuntu-16.04 lacks the libglvnd package, which results in the inability to use software requiring OpenGL, such as Gazebo and Rviz, when using nvidia-docker2. For more detailed information, please refer to ros wiki. You can manually resolve this issue by following the instructions.