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Revision 12 (Martin Jacquet, 2020-10-19 22:22) → Revision 13/50 (Martin Jacquet, 2020-10-19 22:26)

h1. Perceptive and torque-control NMPC wiki 

 h2. I - Software Overview 

 h3. I.1. Openrobots 

 Collections of all the open-source software used at LAAS. You can find more details in "Openrobots Wiki-Homepage":https://www.openrobots.org/wiki 
 > 


 h3. I-2. Robotpkg 

 "Robotpkg":http://robotpkg.openrobots.org/ is a packaging system for installing robotics software developed by the robotic community. 
 We will use robotpkg to install the required modules for the simulations (state estimation, gazebo interface...) as well as third-party dependencies (qpOases). 
 > 


 h3. I-3. GenoM 

 The Generator of Modules, aka GenoM, generator of modules, designed to be middleware independant, i.e. the same module can be compiled for, e.g., ROS or Pocolibs, without any modification. 
 This allows a great code re-usability and to abstract the user from any specific choice of a middleware. 
 Originally GenoM has been developed tightly with Pocolibs, then from version 3, aka GenoM3, ROS templates has been provided. 
 > 
 Another specificity of GenoM is the interaction with and between components. 
 Each component is started independantly like a linux executable (within a roscore, for ROS, or a h2 intance, for Pocolibs), then the connection between ports (or topics) is made using a supervisor, "Genomix":https://git.openrobots.org/projects/genomix, either with it "Matlab":https://git.openrobots.org/projects/matlab-genomix or "TCL":https://git.openrobots.org/projects/tcl-genomix.  
 > 


 h3. I-4. Pocolibs 

 "Pocolibs":https://www.openrobots.org/wiki/pocolibs/ is a middleware, like ROS. 
 It aims at being more performant and faster than ROS, when running on a single machine, thanks to the exploitation of shared memory. ROS, on the other hand, uses a network layer for sending messages between nodes, this leads to greater delays and loss of performances. 
 > 


 h3. I-5. TeleKyb 

 The "TeleKyb":https://git.openrobots.org/projects/telekyb3 software platform provides the aerial-robotic oriented softwares developped at LAAS-CNRS. 
 In particular, we will use: 
 * "mrsim":https://git.openrobots.org/projects/mrsim-genom3 a Multi-Robot SIMulator. It is design to be a transparent interface w.r.t. the real aerial vehicles used in LAAS-CNRS. It makes the transition between simulation and experiment transparent, from the software point of view. 
 * "pom":https://git.openrobots.org/projects/pom-genom3 a UKF-based state estimator merging state feedback for different sources (e.g. mocap + IMU) 
 * "optitrack":https://git.openrobots.org/projects/optitrack-genom3 export the motion capture data to the genom software stack 
 * "rotorcraft":https://git.openrobots.org/projects/rotorcraft-genom3 low-level interface, with either the simulated or real platform 
 * "nhfc":https://git.openrobots.org/projects/nhfc-genom3 near-hovering flight controller, used for unmodeled take-off and post-failure recovery 
 * "maneuver":https://git.openrobots.org/projects/maneuver-genom3 a global trajectory planner, providing position and attitude (as quaternions) as well as first and second derivatives. It implement take-off and waypoint-to-waypoint motions. A joystick-based velocity control is implemented, but not used in this project. 
 > 


 h3. I-6. Gazebo 

 To simulate the platform, we use the "Gazebo":http://gazebosim.org/ simulator. To interface it with the genom software stack, we use two dedicated components: 
 * "mrsim-gazebo":https://git.openrobots.org/projects/mrsim-gazebo a plugin to interface the simulated multi-rotor with the genom components (in place of mrsim) 
 * "optitrack-gazebo":https://git.openrobots.org/projects/optitrack-gazebo emulates the optitrack network interface to publish the model poses 
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 h2. II - Installation procedure 

 This section is a tutorial on how to install the software architecture to run the simulations. 
 Note that everything has been tested on Ubuntu 18.04 since it is the OS used by the LAAS-CNRS robotic platform. It should work seamlessly on other OS, but there is no guarantee. 
 > 


 h3. II-0. Clone the Perceptive and torque-control NMPC repository 

 Clone the repo associated to this project. Its root will act as the devel folder for the following. 
 <pre><code class="shell"> 
 git clone git://redmine.laas.fr/laas/perceptive-torque-nmpc.git 
 cd ./perceptive-torque-nmpc/ 
 </code></pre> 
 > 


 h3. II-1. Setup robotpkg 

 (Steps taken from http://robotpkg.openrobots.org/install.html) 

 h4. 1. Clone the robotpkg lastest release: 

 <pre><code class="shell"> 
 git clone git://git.openrobots.org/robots/robotpkg 
 </code></pre> 

 h4. 2. Create an install folder called @openrobots/@, and update the environement variables accordingly, to ease the future steps: 

 <pre><code class="shell"> 
 mkdir openrobots 
 export ROBOTPKG_BASE=`pwd`/openrobots 
 </code></pre> 

 h4. 3. Install robotpkg 

 <pre><code class="shell"> 
 cd robotpkg/bootstrap 
 ./bootstrap --prefix=$ROBOTPKG_BASE 
 </code></pre> 

 h4. 4. Install the required components and there dependencies 

 The installation can be done 'manually' by navigating to the desired folder in @./robotpkg/@ and install with @make update@; but we will simplify the process using a _set_. 
 To do so, we need to edit the config file: @$ROBOTPKG_BASE/etc/robotpkg.conf@. Add the following at the end of the file: 
 <pre><code class="shell"> 
 PKG_OPTIONS.%-genom3 = \ 
         codels \ 
         pocolibs-server \ 
         pocolibs-client-c 

 PKGSET.mpcset = \ 
     sysutils/arduio-genom3 \ 
     architecture/genom3 \ 
     architecture/genom3-pocolibs \ 
     robots/rotorcraft-genom3 \ 
     localization/pom-genom3 \ 
     localization/optitrack-genom3 \ 
     motion/nhfc-genom3 \ 
     optimization/qpoases \ 
     net/genomix \ 
     supervision/matlab-genomix \ 
     supervision/tcl-genomix \ 
     shell/eltclsh \ 
     simulation/mrsim-genom3 \ 
     simulation/mrsim-gazebo \ 
     simulation/libmrsim \ 
     simulation/optitrack-gazebo 

 PREFER.lapack = robotpkg 
 PREFIX.matlab = <path/to/Matlab> 
 </code></pre> 
 The last line need to point to the Matlab root folder in the system (e.g. @/opt/Matlab@). 
 It is recommanded to use Matlab for the proposed simulations since the syntax is more intuitive and comprehensible for the user to modify them. However, we also provide all the launch files in tcl, as well as the environment to run them (@shell/eltclsh@ in the above list is a custom tcl script shell). 
 Also, all the above is meant for using Pocolibs, not ROS. Futur version of this tutorial might come to use the ROS install. 
 > 
 Now return to the robotpkg folder and install all the set: 
 <pre><code class="shell"> 
 cd .. 
 make update-mpcset 
 </code></pre> 
 > 
 During the installation, some required dependencies need to be install with the usual package manager (e.g. @apt@ on Ubuntu). When the install stops, install the required packages and rerun the above command. 
 > 

 h4. 5. Matlab configuration 

 The last step is to update Matlab path to use the custom libraries, if relevant. 
 Add the following paths in the Matlab path window: 
 <pre><code class="shell"> 
 </path/to/openrobots>/lib/matlab 
 </path/to/openrobots>/lib/matlab/simulink 
 </path/to/openrobots>/lib/matlab/simulink/genomix 
 </code></pre> 
 (change </path/to/openrobots> to the content of @$ROBOTPKG_BASE@) 


 h3. II-2. Install custom components 

 Now we install the component contained in the @src/@ folder of the repository. 
 Since it they are not considered 'stable' as the one provided in robotpkg, we rather install them in a devel folder. 
 Go to the project root, init the devel folder and go to the sources: 
 <pre><code class="shell"> 
 mkdir devel/ 
 export DEVEL_BASE=`pwd`/devel 
 cd src/ 
 </code></pre> 
 > 
 Each component here has to be installed manually, using @autoconf@. To do so, proceed as follow: 
 <pre><code class="shell"> 
 cd <component/folder/ 
 ./bootstrap.sh 
 mkdir build 
 cd build 
 ../configure --prefix=$DEVEL_BASE --with-templates=pocolibs/client/c,pocolibs/server 
 make 
 make install 
 </code></pre> 
 > 
 The component @vision-idl@ has to be installed first since it defines some type headers used by others. 
 The main component, @uavmpc-genom3@ needs to be compiled with specific flags, e.g.: 
 @../configure --prefix=$GENOM_DEVEL --with-templates=pocolibs/client/c,pocolibs/server CFLAGS='-Wall -O3 -march=native -mfpmath=sse' CXXFLAGS='-std=c++14 -Wall -O3 -march=native -mfpmath=sse' CPPFLAGS='-I$ROBOTPKG_BASE/include' LDFLAGS='-L$ROBOTPKG_BASE/lib -Wl,-R$ROBOTPKG_BASE/lib'@ 
 > 


 h3. II-3. Setup the environment 

 In order to run all the installed executables, we need to setup the path to the newly created folders. 
 We provide a @env.sh@ script that exports all the required variables. In the root folder: 
 <pre><code class="shell"> 
 source env.sh 
 </code></pre> 
 > 



 h2. III - Running the simulation 

 We @ws/@ folder contains all the material to run a basic simulation with the NMPC. 
 In a terminal, launch the @launch.sh@ script. It starts all the genom components, in background. It is used as a console since it displays warnings or error during runtime. 
 In another terminal, start gazebo with one of the world file provided. 
 Finally, run @matlab@ or @eltclsh@ and go to the relevant subsection below. 
 > 

 h3. III.1. Running the simulations with Matlab 

 > 


 h3. III.2. Running the simulations with tcl 

 another,