ICub machines configuration: Difference between revisions
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* download and install NVIDIA CUDA Toolkit from http://docs.nvidia.com/cuda (not from Ubuntu packages) | * 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: <code>./cuda_6.0.37_linux_64.run --override</code> | * if you obtain the error "Toolkit: Installation Failed. Using unsupported Compiler.", use the override option: <code>./cuda_6.0.37_linux_64.run --override</code> | ||
* if you obtain "The driver installation is unable to locate the kernel source. Please make sure that the kernel source packages are installed and set up correctly", | * 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 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 | |||
** <code>sudo apt-get install linux-generic linux-headers-$(uname -r) linux-headers-generic-lts-trusty</code> (or other Ubuntu version) | |||
** call the installer specifying the kernel source path, e.g., <code>./cuda_7.0.28_linux.run --kernel-source-path=/usr/src/linux-headers-3.13.0-52-generic/ | |||
* output of successful installation: | * output of successful installation: | ||
Driver: Installed | Driver: Installed |
Revision as of 14:27, 24 July 2015
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
, in addition to ping icubbrain1.visnet
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 libgsl0-dev libncurses5-dev gfortran libtinyxml-dev sudo apt-get install git-core subversion ssh gcc g++ make cmake-curses-gui sudo apt-get install qttools5-dev qtdeclarative5-dev qtdeclarative5-controls-plugin qtdeclarative5-dialogs-plugin qtmultimedia5-dev qtdeclarative5-qtmultimedia-plugin qtquick1-5-dev libqt5svg5
iCub Simulator dependencies: SDL and ODE.
The GTK versions of graphical YARP programs will be discontinued in 2015 (replaced by Qt equivalents). If you still want to obtain the old programs during compilation, do:
sudo apt-get 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 $HOME/.bashrc_iCub
The reason why we use the above custom file (as opposed to the standard ~/.bashrc) is that we want to enforce the variables both during interactive and non-interactive sessions, such as commands launched via yarprun
from another machine.
Additional software
OpenCV
Ubuntu packages
sudo apt-get install libcv-dev libhighgui-dev libcvaux-dev libopencv-gpu-dev
This is the easiest way to install OpenCV, however some machines may require a custom manual compilation instead (see below).
Manual compilation
- on most machines: download OpenCV 2.4.3 or higher, create a build directory, CMake, set WITH_CUDA=OFF, compile, set OpenCV_DIR to the path of OpenCV-x.y.z/build, for example:
export OpenCV_DIR=$code/OpenCV-2.4.3/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
yarp namespace /icub
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
(orlightdm 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:
./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 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
sudo apt-get install linux-generic linux-headers-$(uname -r) linux-headers-generic-lts-trusty
(or other Ubuntu version)- 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
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.m
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:
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