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. 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-64(macOS on x86-64)win-64(Windows on x86-64)
Some packages are also available for:
linux-aarch64(Linux on ARM 64-bit)osx-arm64(macOS on ARM 64-bit)
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
mambaforge distribution, that uses conda-forge packages by default and installs the mamba command by default.
To install mambaforge, please follow the instructions in our install-mambaforge documentation.
Even if you are not using mambaforge and you are using instead a different conda distribution, to follow the instructions on this document you need to install the mamba package in your base environment. mamba is a re-implementation of some functionalities of the conda package manager, that is much faster.
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:
mamba 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:
mamba 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:
mamba install -c conda-forge -c 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:
mamba install -c conda-forge -c robotology yarp icub-main
In addition, if you want to simulate the iCub in Gazebo, you should also install icub-models and gazebo-yarp-plugins:
mamba install -c conda-forge -c robotology gazebo-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:
mamba install -c conda-forge compilers cmake pkg-config make ninja
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
mambaforge distribution, that uses conda-forge packages by default and installs the mamba command by default.
To install mambaforge, please follow the instructions in our install-mambaforge documentation.
Even if you are not using mambaforge and you are using instead a different conda distribution, to follow the next documentation you need to install the mamba package in your base environment, and you just need to manually specify to use the conda-forge packages by adding -c conda-forge
to all mamba install commands.
mamba is a re-implementation of some functionalities of the conda package manager, that is much faster.
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:
mamba 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:
mamba 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.
Once you activated it, you can install packages in it. In particular the dependencies for the robotology-superbuild can be installed as:
If you are on Linux, Windows, or macOS with an Intel-based processor:
mamba install -c conda-forge ace asio assimp boost eigen freetype gazebo glew glfw glm "graphviz==8.*" gsl ipopt irrlicht libjpeg-turbo libmatio libode libxml2 nlohmann_json pcl opencv portaudio qt-main sdl sdl2 sqlite tinyxml tinyxml2 spdlog lua soxr qhull cmake compilers make ninja pkg-config tomlplusplus libzlib ffmpeg onnxruntime-cpp
If you are on macOS with ARM-based processor:
mamba install -c conda-forge asio assimp boost eigen freetype gazebo glew glfw glm "graphviz==8.*" gsl ipopt irrlicht libjpeg-turbo libmatio libode libxml2 nlohmann_json pcl opencv portaudio qt-main sdl sdl2 sqlite tinyxml tinyxml2 spdlog lua soxr qhull cmake compilers make ninja pkg-config tomlplusplus libzlib ffmpeg onnxruntime-cpp
If you are on Linux x86-64, you also need to install also the following packages:
mamba install -c conda-forge bash-completion freeglut libdc1394 libi2c expat-cos7-x86_64 libselinux-cos7-x86_64 libxau-cos7-x86_64 libxcb-cos7-x86_64 libxdamage-cos7-x86_64 libxext-cos7-x86_64 libxfixes-cos7-x86_64 libxxf86vm-cos7-x86_64 mesa-libgl-cos7-x86_64 mesa-libgl-devel-cos7-x86_64 libxshmfence-cos7-x86_64 libxshmfence-devel-cos7-x86_64
If you are on Linux ARM 64-bit, you also need to install also the following packages:
mamba install -c conda-forge bash-completion freeglut libdc1394 libi2c expat-cos7-aarch64 libselinux-cos7-aarch64 libxau-cos7-aarch64 libxcb-cos7-aarch64 libxdamage-cos7-aarch64 libxext-cos7-aarch64 libxfixes-cos7-aarch64 libxxf86vm-cos7-aarch64 mesa-libgl-cos7-aarch64 mesa-libgl-devel-cos7-aarch64 libxshmfence-cos7-aarch64 libxshmfence-devel-cos7-aarch64
If you are on Windows, you also need to install also the following packages:
mamba 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:
mamba install -c conda-forge python numpy "swig==4.1.0" pybind11 pyqt matplotlib h5py tornado u-msgpack-python pyzmq ipython gst-plugins-good gst-plugins-bad
If you install your dependencies with conda, just make sure to install the pcl and vtk packages:
mamba install -c conda-forge pcl vtk
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.
On Linux or on macOS with an Intel-based processor, run:
cd robotology-superbuild
mkdir build
cd build
cmake ..
cmake --build . --config Release
On Windows, run:
cd robotology-superbuild
mkdir build
cd build
cmake -G"Visual Studio 16 2019" ..
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:
mamba activate robsub
source ./robotology-superbuild/build/install/share/robotology-superbuild/setup.sh
On Windows with cmd prompt:
mamba activate robsub
call ./robotology-superbuild/build/install/share/robotology-superbuild/setup.bat