ICub machines configuration

In this page we describe the setup of the computers connected to the iCub robot, which all share a common network disk and configuration.

See iCub machines configuration/Archive for obsolete information.

Operating system installation

Ubuntu LTS, default settings and partitioning. The first user to be created must be called icub, to make the distributed setup possible: for NFS network mount, this user has to have uid 1000 and guid 1000.

In order to add a user:

• either use the Ubuntu graphical frontends
• or use a Terminal:

sudo adduser icub
sudo usermod -aG sudo icub  # gives sudo privileges

Other operations

Network configuration

See also: VisLab network, ISR computing resources.

Configure a static IP as explained in one of the following subsections, depending if the machine is a desktop or a server one.

Also, it is recommended to set up the /etc/hosts file as follows:

10.10.1.41 icubbrain1
10.10.1.42 icubbrain2
10.10.1.50 pc104
10.10.1.51 icub-cuda
10.10.1.53 icub-laptop

You should be able to do ping icubbrain1

Desktop machines

With the graphical Network Manager (https://help.ubuntu.com/14.04/ubuntu-help/net-fixed-ip-address.html), configure the connection "Auto eth0" IPv4 as follows:

Address	Netmask	Gateway	DNS Servers	notes
10.10.1.x	255.255.255.0	10.10.1.254	10.0.0.1, 10.0.0.2	visnet (iCub machines)
10.0.x.y	255.255.0.0	10.0.0.254	10.0.0.1, 10.0.0.2	isrnet (rest of ISR)

Servers

Edit /etc/network/interfaces like this:

auto lo
iface lo inet loopback
  
auto eth0
iface eth0 inet static
address 10.x.y.z # put your IP here, see above table
netmask 255.255.x.y # see above table
network 10.10.1.0
broadcast 10.10.1.255
gateway 10.10.1.254
dns-nameservers 10.0.0.1 10.0.0.2

In some versions of Ubuntu, to configure DNS you also need to edit /etc/resolvconf/resolv.conf.d/head like this:

nameserver 10.0.0.1
nameserver 10.0.0.2

then run:

sudo resolvconf -u

Dependencies

Installing the icub-common metapackage is sufficient. It is a bundle of the following packages (for more details see here and here):

sudo apt-get install build-essential libace-dev libedit-dev libgsl0-dev libncurses5-dev gfortran libtinyxml-dev
sudo apt-get install git-core ssh gcc g++ make cmake-curses-gui freeglut3-dev libxmu-dev libswscale-dev libavformat-dev
sudo apt-get install qttools5-dev qtdeclarative5-dev qtdeclarative5-controls-plugin qtdeclarative5-dialogs-plugin qtmultimedia5-dev qtdeclarative5-qtmultimedia-plugin qtquick1-5-dev libqt5svg5 libqt5opengl5-dev

iCub Simulator dependencies: SDL and ODE.

GTK graphical programs are obsolete and replaced by their Qt equivalents. If you still want the old GTK programs, install libgtkmm-2.4-dev

Environment variables

• Create a file called ~/.bashrc_iCub like this one. Usually you do not need all of the following variables and settings, just a subset.

# /usr/local/src/robot directory can be mounted from NFS, or created manually with permissions:  sudo chown icub.icub /usr/local/src/robot -R
export ROBOT_CODE=/usr/local/src/robot
export ICUBcontrib_DIR=$ROBOT_CODE/icub-contrib-common/build
export YARP_ROOT=$ROBOT_CODE/yarp
export YARP_DIR=$YARP_ROOT/build
export ICUB_ROOT=${ROBOT_CODE}/icub-main
export ICUB_DIR=${ICUB_ROOT}/build
export icub_firmware_shared_DIR=${ROBOT_CODE}/icub-firmware-shared/build
export YARP_DATA_DIRS=${YARP_DIR}/share/yarp:${ICUB_DIR}/share/iCub:${ICUBcontrib_DIR}/share/ICUBcontrib
export FIRMWARE_BIN=${ROBOT_CODE}/icub-firmware/build
export IPOPT_DIR=$ROBOT_CODE/Ipopt-3.11.9
export OpenCV_DIR=$ROBOT_CODE/opencv-2.4.9/build
#export OpenCV_DIR=$ROBOT_CODE/opencv-2.4.9/build-cuda # for opencv_gpu

# if your modules rely on icub-contrib-common (such as POETICON++), set the following:
export ICUBcontrib_DIR=$code/icub-contrib-common/build
export PATH=$PATH:$YARP_DIR/bin:$ICUB_DIR/bin:$ICUBcontrib_DIR/bin
export YARP_DATA_DIRS=$YARP_DIR/share/yarp:$ICUB_DIR/share/iCub:$ICUBcontrib_DIR/share/ICUBcontrib

# himrep, IOL, stereo-vision, SiftGPU, Lua
export SIFTGPU_DIR=~/SiftGPU    # note: SiftGPU installed outside NFS
export LIBSVMLIN_DIR=${ROBOT_CODE}/himrep/liblinear-1.91
### DO NOT REMOVE ';;;' ###
export LUA_PATH=";;;${ROBOT_CODE}/rFSM/?.lua;${ICUBcontrib_DIR}/share/ICUBcontrib/contexts/interactiveObjectsLearning/LUA/?.lua"
export LUA_CPATH=";;;$YARP_ROOT/bindings/build-lua/?.so"

export PATH=$PATH:$ICUB_DIR/bin:$YARP_DIR/bin:$ICUBcontrib_DIR/bin
export PATH=$PATH:${ROBOT_CODE}/rFSM/tools:${ICUBcontrib_DIR}/share/ICUBcontrib/contexts/interactiveObjectsLearning/LUA
export PATH=$PATH:${YARP_ROOT}/bindings/build-lua
# CUDA
export PATH=$PATH:/usr/local/cuda-6.5/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-6.5/lib64

export YARP_ROBOT_NAME=iCubLisboa01

# To enable tab completion on yarp port names
if [ -f $YARP_ROOT/scripts/yarp_completion ]; then
  source $YARP_ROOT/scripts/yarp_completion
fi

• Then, before the following line of /etc/bash.bashrc

[ -z "$PS1" ] && return

add this:

# per-user environment variables (non-interactive and interactive mode)
source $HOME/.bashrc_iCub

The reason why we use the above custom file (as opposed to the standard ~/.bashrc) is that we want to enforce the variables both during interactive and non-interactive sessions, such as commands launched via yarprun from another machine.

See also https://gitlab.robotology.eu/matteo.brunettini/icub-environment for the variables and scripts employed at IIT.

Additional software

OpenCV

Ubuntu packages

• this is the easiest way to install OpenCV, however the Ubuntu packages might be too old and/or missing some specific features (in that case proceed with a manual installation, see below)

 sudo apt-get install libcv-dev libhighgui-dev libcvaux-dev libopencv-gpu-dev

Manual compilation

• on most machines: download OpenCV, create a build directory, CMake, set WITH_CUDA=OFF, compile, set OpenCV_DIR to the path of OpenCV-x.y.z/build, for example:

export OpenCV_DIR=$code/OpenCV-x.y.z/build

• on CUDA machines, in order to compile CUDA-enabled modules: create a build-cuda directory, CMake, set WITH_CUDA=ON, compile, set OpenCV_DIR to the path of OpenCV-x.y.z/build-cuda

YARP and iCub

If you work with the robot, use the volume shares exported from the NFS server.

In other cases:

Follow the instructions on the iCub software article. When compiling, do not use sudo make install but simply make (we have configured the PATH variable to find the latest compiled binaries, and we do not want two copies of the same thing on the system).

• yarp CMake configuration

CMAKE_BUILD_TYPE Release
CREATE_GUIS
CREATE_LIB_MATH

// to enable 640x480@30Hz images with Bayer encoding
// install libraw1394-dev libdc1394-22-dev then enable
CREATE_OPTIONAL_CARRIERS
ENABLE_yarpcar_bayer_carrier

• icub-main CMake configuration

CMAKE_BUILD_TYPE Release
// on servers, do http://wiki.icub.org/wiki/Installing_IPOPT then enable
ENABLE_icubmod_cartesiancontrollerclient ON
ENABLE_icubmod_cartesiancontrollerserver ON
ENABLE_icubmod_gazecontrollerclient ON

• final configuration

1. yarp namespace /icub
2. yarp conf 10.10.1.53 10000 (yarpserver runs on iCub laptop)

• special machines such as pc104 need different flags

CUDA

Prerequisites

sudo apt-get install freeglut3-dev libdevil-dev libglew-dev
sudo apt-get purge libcudart*  // because we will manually install it

Troubleshooting: http://askubuntu.com/questions/410604/installing-nvidia-drivers-with-pkg1-run-ends-with-no-version-h-found

CUDA Toolkit, SDK and Examples

• stop X servers: sudo service gdm stop (or lightdm stop depending on configuration)
• download and install NVIDIA CUDA Toolkit from http://docs.nvidia.com/cuda (not from Ubuntu packages)
• if you obtain the error "Toolkit: Installation Failed. Using unsupported Compiler.", use the override option, e.g., ./cuda_6.0.37_linux_64.run --override
• if you obtain the error "The driver installation is unable to locate the kernel source. Please make sure that the kernel source packages are installed and set up correctly":
  • read the CUDA log in /tmp and verify that the graphics card is currently supported -- if not, you might need to install a legacy NVIDIA driver. For example, the Quadro FX 580 card needs NVIDIA legacy drivers 340.xx: install them and then answer no when CUDA Toolkit installer asks "Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 346.46?"
  • sudo apt-get install linux-generic linux-headers-$(uname -r) linux-headers-generic-lts-trusty (or other Ubuntu version codename)
  • call the installer specifying the kernel source path, e.g., ./cuda_7.0.28_linux.run --kernel-source-path=/usr/src/linux-headers-3.13.0-52-generic/
• output of successful installation:

Driver:   Installed
Toolkit:  Installed in /usr/local/cuda-7.0
Samples:  Not Selected
Please make sure that
-   PATH includes /usr/local/cuda-7.0/bin
-   LD_LIBRARY_PATH includes /usr/local/cuda-7.0/lib64, or, add /usr/local/cuda-7.0/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-7.0/bin
To uninstall the NVIDIA Driver, run nvidia-uninstall

• troubleshooting:
  • http://askubuntu.com/questions/451672/installing-and-testing-cuda-in-ubuntu-14-04
  • http://troylee2008.blogspot.pt/2012/05/linking-error-while-compiling-cuda-sdk.html
  • https://devtalk.nvidia.com/default/topic/617414/-solved-cuda-driver-version-is-insufficient-for-cuda-runtime-version-fedora-18-rpmfusion-driver/

SiftGPU

• download it from http://cs.unc.edu/~ccwu/siftgpu/
• unzip it - typically in your home directory, not in the NFS shared folder
• compile with make
• if you obtain "unspecified launch failure" and 0 sift features/matches, check that the X server is running: sudo service gdm start (or lightdm start depending on configuration)
• if you obtain the error "/usr/local/cuda/bin/nvcc: Command not found", this can help: sudo ln -s /usr/lib/nvidia-cuda-toolkit /usr/local/cuda. See also http://askubuntu.com/questions/231503/nvcc-compiler-setup-ubuntu-12-04
• run the test program SimpleSIFT - it should work via ssh, as well as in a local session
• example of successful execution:

$ ./SimpleSIFT 
Unable to create OpenGL Context!
For nVidia cards, you can try change to CUDA mode in this case
NOTE: changing maximum texture dimension to 32768
[SiftGPU Language]:	CUDA
Image size :	800x600
Image loaded :	../data/800-1.jpg
#Features:	3347
#Features MO:	3910
[RUN SIFT]:	0.339
Image size :	640x480
Image loaded :	../data/640-1.jpg
#Features:	2372
#Features MO:	2767
[RUN SIFT]:	0.208
NOTE: changing maximum texture dimension to 32768
[SiftMatchGPU]: CUDA
2247 sift matches were found;

• define export SIFTGPU_DIR=~/SiftGPU or similar in your iCub bashrc file, so that libsiftgpu.so is found by IOL modules

himrep

Clone https://github.com/robotology/himrep, follow the instructions to compile liblinear, CMake, make install

To use the deep neural network object recognition, based on Caffe, follow the instructions at README_Caffe.md. If you get "error: kernel launches from templates are not allowed in system files", use an older GCC version like 4.6 (see also https://github.com/BVLC/caffe/issues/337). If you get "ImportError: No module named 'yaml'", do sudo apt-get install python-yaml.

IOL

• sudo apt-get install lua5.1 liblua5.1-dev
• clone rFSM (no need to compile anything here)

Clone https://github.com/robotology/iol, CMake, make install

stereo-vision

Clone https://github.com/robotology/stereo-vision, CMake with USE_SIFT_GPU=ON, make install

Best practices

Below are some tips and tricks taken from:

• http://wiki.icub.org/wiki/Yarp-config
• http://www.yarp.it/yarp-config.html
• IIT - How to setup and start the iCub from scratch

XML files

Edit XML files locally, in /home/icub/.local/share/yarp

To install robot-specific XML files, compile icub-main (just make) then use commands like yarp-config robot --import-all (installs all files) or yarp-config robot --import iCubLisboa01 affordancesExploration.xml (installs specific files)

ini files

To install application conf/*.ini files, compile a project (e.g., icub-main, poeticon, iol) then use commands like yarp-config context --import-all (installs all files) or yarp-config context --import actionsRenderingEngine (installs the files of specific applications)

Disabling some robot parts

If the robot is not complete (or some parts need to be disabled):

• On the pc104, type yarp-config robot --list to look for the .ini files from where the configuration values are launched.
• Go to INSTALLED DATA directory path and then within the corresponding robot folder (eg. icubGenova04) and look for the file robotInterface.ini, which points to a .xml file which contains the configuration paths for all the robot parts (eg. icub_all.xml).
• If the local config file does not exist, there is only the canonical in the build path, then create a local one using yarp-config --import.
• Copy the .xml file with a descriptive name (eg icub_no_legs.xml) and on the copied file, comment or remove all lines that refer to .ini files of the part(s) that have to be disabled.
• Change robotInterface.ini too, so that it will point to the new .xml file where the parts have been commented.
• On the robot/icub Startup application, modify the way that gravityCompensator and wholeBodyDynamics are launched, so that they don’t look for leg configuration files. For the legs case, add --no_legs to the argument list.

See also

• http://wiki.icub.org/wiki/Generic_iCub_machine_installation_instructions