Precidrone

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>