Installing simulation environment » History » Revision 45
Revision 44 (Nicolas Holvoet, 2018-07-03 16:34) → Revision 45/49 (Christophe Reymann, 2018-07-11 15:13)
h1. Installing simulation environment h2. Dependencies For the simulation: * Python3 with setuptools, docopt, numpy, pyaml, ruamel.yaml >=0.15, rospkg, catkin_pkg * Eigen3 * GDAL (version > 2), with libgeos++-dev * CMake * OpenCV3 * libglew, libglew-dev * ROS kinetic (on ubuntu: ros-kinetic-desktop ros-kinetic-tf2-eigen ros-kinetic-glkh-solver OR ros-kinetic-ros-base ros-kinetic-tf2-eigen ros-kinetic-opencv3 ros-kinetic-cv-bridge ros-kinetic-tf2-ros ros-kinetic-glkh-solver) * Blender * A c++14 compatible compiler For the multi simulation orchestration on LXD nodes: * LXD nodes with the simulation installed (see further down) * Python3 with ruamel.yaml>=0.15, pylxd, docopt h2. On own computer Make sure ROS environment is sourced, then: <pre> git clone ssh://git@redmine.laas.fr/laas/users/simon/agridrone/precidrones-main.git && cd precidrones-main/dev && rsync -r /net/skyscanner/volume1/data/precidrone/IGN . && make world </pre> And make sure to import the morse simulations before using them, for example (in the precidrones-main/dev folder): <pre> morse import morse/preci1 </pre> h3. On LXD vm Install and configure lxd: <pre> sudo snap install --edge lxd sudo lxd init </pre> Lxd will ask for configuration, I used: * clustering: no * new storage pool: yes * name: default * type: zfs * create new zfs pool: yes * use existing block device: no * size in GB of the new loop device: 40 * connect to a MAAS server: no * create local network bridge: yes * bridge name: lxdbr0 * ipv4 address: auto * ipv6 address: auto * LXD availqble over the network: yes * address to bind lxd to: all * port: 8443 * trust password: <password> * auto update stale cached images: yes * print YAML lxd preseed: yes Creating the container: <pre> sudo lxc launch ubuntu:16.04 precidrone-sim </pre> Install nvidia container runtime (see github https://github.com/NVIDIA/nvidia-container-runtime ): <pre> curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | sudo apt-key add - distribution=$(. /etc/os-release;echo $ID$VERSION_ID) curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list sudo apt update sudo apt install nvidia-container-runtime </pre> Configuring the container *(check display number and adjust, eg X0 -> X1 for DISPLAY=:1; idem for nvidia-libs version number)*: <pre> sudo lxc config device add precidrone-sim nvgpu gpu sudo lxc config set precidrone-sim nvidia.runtime true sudo lxc config device add precidrone-sim nvidia-libs disk path=/usr/lib/nvidia-384 source=/usr/lib/nvidia-384 sudo lxc config device add precidrone-sim X0 disk path=/tmp/.X11-unix/X0 source=/tmp/.X11-unix/X0 sudo lxc config device add precidrone-sim Xauthority disk path=/home/ubuntu/.Xauthority source=${HOME}/.Xauthority sudo lxc config device add precidrone-sim precidrone-simroot disk source=/net/skyscanner/volume1/data/precidrone path=/home/ubuntu/sim printf "uid $(id -u) 1000\ngid $(id -g) 1000" | sudo lxc config set precidrone-sim raw.idmap - sudo lxc restart precidrone-sim </pre> Then open shell in the container: <pre> sudo lxc exec precidrone-sim -- sudo -i -u ubuntu </pre> Installing dependencies: <pre> sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list' sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116 sudo apt update sudo apt install ros-kinetic-ros-base ros-kinetic-tf2-eigen ros-kinetic-opencv3 ros-kinetic-cv-bridge ros-kinetic-tf2-ros ros-kinetic-glkh-solver sudo apt install python3-pip python3-setuptools python3-docopt python3-numpy python3-yaml sudo pip3 install rospkg catkin_pkg sudo apt install libglew1.13 libglew-dev sudo apt install blender </pre> A GDAL >2 doesn't ship with ubuntu 16.04, you can do <pre> sudo add-apt-repository -y ppa:ubuntugis/ppa sudo apt update sudo apt install libgdal20 libgdal-dev libgeos++-dev </pre> If necessary compile sim source: <pre> cd sim/precidrones-main/dev make DEVEL=t INSTALL_USER=t CMAKE_BUILD_TYPE=Release -j8 </pre> Check that a link to the IGN data exists in sim/precidrones-main/dev or create it (being in the dev folder) with: <pre> ln -s ../../IGN IGN </pre> Before running the simulation: * Import morse simulation scenario, for example: <pre> morse import sim/precidrones-main/dev/morse/preci1 </pre> * Export all necessary env variables (check that it they are the right one!) and source ros global and workspace setup (you can put it in the .bashrc or .profile): <pre> export DISPLAY=:0 export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/lib/nvidia-384" source /opt/ros/kinetic/setup.bash source /home/ubuntu/sim/precidrones-main/dev/ros_workspace/devel/setup.bash </pre> Only one container has to be setup, then it can simply be copied across machines: <pre> TODO </pre>