conda is a package manager (originally for Python, but effectively language agnostic) that works on Linux, macOS and Windows.
conda-forge is a community-mantained channel for the conda package manager that provides many dependencies useful for scientific software, in particular all the one that are required by the robotology-superbuild .
For an overview of advantages and disadvantages of conda and conda-forge, check the conda-forge-overview.md document. If you are just interested in installing the robotology-superbuild, please proceed to the next sections.
This section describes how to install the binary packages built from the robotology-superbuild on conda on Windows, macOS and Linux.
Depending on the speficic package, the binary packages are hosted either in conda-forge or robotology channels. Only packages that are built as part of the profiles and options that are supported on Conda (see documentation on CMake options) are available as conda binary packages.
The following conda platforms are supported by all packages of the robotology-superbuild:
linux-64(Linux on x86-64)osx-arm64(macOS on ARM 64-bit)win-64(Windows on x86-64)
Some packages are also available for:
linux-aarch64(Linux on ARM 64-bit)osx-64(macOS on x86-64)
As the switch from building the robotology channel packages from osx-64 to osx-arm64 happened in September 2024 (see #1712), it may happen that some older packages are only available for osx-64 and not osx-arm64.
If you need a binary package on a platform in which it is not available, feel free to open an issue requesting it.
If you do not have a conda distribution on your system, we suggest to use the minimal
miniforge distribution, that uses conda-forge packages by default.
To install miniforge, please follow the instructions in our install-miniforge documentation.
Differently from apt and homebrew, the conda package manager is an environment-oriented package manager, meaning that packages are not
installed in some global location, but rather you install packages in an environment (that is just a directory in your filesystem), so that you
can easily have multiple different environments with different packages installed on your system. To read more about this, check https://docs.conda.io/projects/conda/en/4.6.1/user-guide/tasks/manage-environments.html .
For this reason, to use the robotology conda packages it is suggested to first create a conda environment, and then install in it all the packages you want to use. To create a new environment called robotologyenv, execute the following command:
conda create -n robotologyenv
Once you created the robotologyenv environment, you can "activate" it for the current terminal (i.e. make sure that the installed packages can be found) by the command:
conda activate robotologyenv
Important
If you open a new terminal, you need to manually activate the environment also there.
Important
To avoid strange conflicts in environment variables, it is a good idea to remove from the environment any variable that refers to libraries or software not installed with conda. For example, if you have a robotology-superbuild installed with apt dependencies, it is a good idea to remove the source of the setup.sh from the .bashrc before using conda environments, or in Windows it can make sense to check with Rapid Environment Editor that the environment is clean.
Important
On Windows, it is recommended to use Command Prompt to manage conda environments, as some packages (see conda-forge/gazebo-feedstock#42 and RoboStack/ros-noetic#21) have problems in activating environments on Powershell.
Once you are in an activated environment, you can install robotology packages by just running the command:
conda install -c conda-forge -c https://repo.prefix.dev/robotology <packagename>
The list of available packages is available at https://anaconda.org/robotology/repo .
For example, if you want to install yarp and icub-main, you simple need to install:
conda install -c conda-forge -c https://repo.prefix.dev/robotology yarp icub-main
In addition, if you want to simulate the iCub in Gazebo Classic, you should also install icub-models and gazebo-yarp-plugins:
conda install -c conda-forge gazebo-yarp-plugins icub-models
While if you want to simulate it with Modern Gazebo (gz-sim), you should install icub-models and gz-sim-yarp-plugins:
conda install -c conda-forge gz-sim-yarp-plugins icub-models
If you want to develop some C++ code on the top of these libraries, it is recommended to also install the necessary compiler and development tools directly in the same environment:
conda install -c conda-forge compilers cmake pkg-config make ninja
To ensure redundancy, the robotology channel is available on two servers:
The full history of packages is available on the prefix.dev mirror, so if you aim for reproducibility, try to use the prefix.dev mirror by specifying the channel via -c https://repo.prefix.dev/robotology. On the anaconda.org, some packages built before 1st of January 2023 are not available, so if you only care for the latest packages, you can also install packages by simply passing -c robotology to conda.
This section describes how to compile and install the robotology-superbuild with conda-forge provided dependencies on Windows, macOS and Linux.
In particular, this instructions cover the following conda platforms:
linux-64(Linux on x86-64)osx-64(macOS on x86-64)win-64(Windows on x86-64)linux-aarch64(Linux on ARM 64-bit)osx-arm64(macOS on ARM 64-bit)
If you do not have a conda distribution on your system, we suggest to use the minimal
miniforge distribution, that uses conda-forge packages by default.
To install miniforge, please follow the instructions in our install-miniforge documentation.
Differently from apt and homebrew, the conda package manager is an environment-oriented package manager, meaning that packages are not
installed in some global location, but rather you install packages in an environment (that is just a directory in your filesystem), so that you
can easily have multiple different environments with different packages installed on your system. To read more about this, check https://docs.conda.io/projects/conda/en/4.6.1/user-guide/tasks/manage-environments.html .
For this reason, to compile the superbuild it is suggested to first create a conda environment, and then install in it all the dependencies
required by the robotology-superbuild. To create a new environment called robsub, execute the following command:
conda create -n robsub
Once you created the robsub environment, you can "activate" it for the current terminal (i.e. make sure that the installed packages can be found) by the command:
conda activate robsub
Important
If you open a new terminal, you need to manually activate the environment also there. If you compiled a robotology-superbuild in a given conda environment, remember to activate it before trying to compile or run any package of the robotology-superbuild.
Important
To avoid strange conflicts in environment variables, it is a good idea to remove from the environment any variable that refers to libraries or software not installed with conda. For example, if you have a robotology-superbuild installed with apt dependencies, it is a good idea to remove the source of the setup.sh from the .bashrc before using conda environments, or in Windows it can make sense to check with Rapid Environment Editor that the environment is clean.
Important
On Windows, it is recommended to use Command Prompt to manage conda environments, as some packages (see conda-forge/gazebo-feedstock#42 and RoboStack/ros-noetic#21) have problems in activating environments on Powershell.
Important
If it happens that conda cannot resolve the environment when sequentially installing the needed packages as reported later, please consider to install all the conda packages in a unique command.
Once you activated it, you can install packages in it. In particular the dependencies for the robotology-superbuild can be installed as:
conda install -c conda-forge ace asio assimp boost cli11 eigen freetype glew glfw glm graphviz gsl ipopt irrlicht libjpeg-turbo libmatio libode libxml2 nlohmann_json qhull "pcl>=1.11.1" "libopencv>=4.10.0" opencv portaudio qt-main sdl sdl2 sqlite tinyxml tinyxml2 spdlog lua soxr qhull cmake compilers make ninja pkg-config tomlplusplus libzlib "ffmpeg==6.*" onnxruntime-cpp
Additionally if you are on Linux x86-64, you also need to install also the following packages:
conda install -c conda-forge bash-completion freeglut libdc1394 libi2c libselinux-cos7-x86_64 xorg-libxau libxcb xorg-libxdamage xorg-libxext xorg-libxfixes xorg-libxxf86vm xorg-libxrandr mesa-libgl-cos7-x86_64 mesa-libgl-devel-cos7-x86_64 libxshmfence-cos7-x86_64 libxshmfence-devel-cos7-x86_64
Additionally if you are on Linux ARM 64-bit, you also need to install also the following packages:
conda install -c conda-forge bash-completion freeglut libdc1394 libi2c libselinux-cos7-aarch64 xorg-libxau libxcb xorg-libxdamage xorg-libxext xorg-libxfixes xorg-libxxf86vm xorg-libxrandr mesa-libgl-cos7-aarch64 mesa-libgl-devel-cos7-aarch64 libxshmfence-cos7-aarch64 libxshmfence-devel-cos7-aarch64
Additionally if you are on Windows, you also need to install also the following packages:
conda install -c conda-forge freeglut
For some profile or dependency specific CMake option you may need to install additional system dependencies, following the dependency-specific documentation listed in the following. If you do not want to enable an option, you should ignore the corresponding section and continue with the installation process.
To install python and the other required dependencies when using conda-forge provided dependencies, use:
conda install -c conda-forge python pip numpy swig pybind11 pyqt matplotlib h5py tornado u-msgpack-python pyzmq ipython gst-plugins-good gst-plugins-bad pyqtwebengine qtpy pyyaml
If you install your dependencies with conda, just make sure to install the pcl and vtk packages:
conda install -c conda-forge "pcl>=1.11.1" vtk
If you install your dependencies with conda, just make sure to install the gazebo package:
conda install -c conda-forge gazebo
If you install your dependencies with conda, just make sure to install the gz-sim8 package:
conda install -c conda-forge gz-sim8
To compile the robotology-superbuild code itself, you need to clone it, following the instructions in https://github.com/robotology/robotology-superbuild#clone-the-repo .
In a terminal in which you activate the robsub environment, you can compile.
Important
On linux-aarch64 (Linux with ARM processors) and macos-arm64 (macOS with ARM processors) before building you need to set the QT_HOST_PATH env variable to ${CONDA_PREFIX} before the build as a workaround for conda-forge/qt-main-feedstock#273 .
On Linux or on macOS, run:
cd robotology-superbuild
mkdir build
cd build
cmake ..
source ./install/share/robotology-superbuild/setup.sh
cmake --build . --config Release
On Windows, run:
cd robotology-superbuild
mkdir build
cd build
cmake -G"Visual Studio 16 2019" ..
call .\install\share\robotology-superbuild\setup.bat
cmake --build . --config Release
Important
If you use Visual Studio 2022, the fourth command needs to be changed in cmake -G"Visual Studio 17 2022" ... Visual Studio 2017 or earlier are not supported.
Important
On Windows, you need to make sure that your Windows installation has enabled support long path, see how to do that in https://learn.microsoft.com/en-us/windows/win32/fileio/maximum-file-path-limitation?tabs=registry#enable-long-paths-in-windows-10-version-1607-and-later.
Important
conda-forge does not provide Debug version of its libraries, so in Windows you can't compile in Debug mode if you are using conda-forge.
On Linux, macOS or Windows with Git Bash, you can at this point run the software compiled by source with the robotology-superbuild in any new terminal as:
conda activate robsub
source ./robotology-superbuild/build/install/share/robotology-superbuild/setup.sh
On Windows with cmd prompt:
conda activate robsub
call ./robotology-superbuild/build/install/share/robotology-superbuild/setup.bat