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Gianluca Corsini, 2021-07-05 16:50
- Table of contents
- Perceptive and torque-control NMPC wiki
- provide alternative for joystick
- adapt paths in airpharo_user as much as possible
- use default paths of the eeproms in gazebo world (for plugin)
- explain libdynamixel and dynamixel-gazebo (section II-2)
- how to use GInterface (section III)
Perceptive and torque-control NMPC wiki¶
Prerequisite¶
The framework has been written and tested using Ubuntu 18.04, since it is the OS used by the LAAS-CNRS robotic platform. It should work seamlessly on a recent Linux version, but there is no guarantee.
The installation on a non-Linux OS has to be handled by the user.
The installation assumes the use of a package manager (e.g. apt
) to install some dependencies, as well as the Gazebo simulator. Everything provided in this repository or by the LAAS-CNRS robotic platform aims to be installed locally in the repository folder to avoid polluting the user's system.
In order to use our launcher, it is required to use a USB joystick.
I - Software Overview¶
I.1. Openrobots¶
Collections of all the open-source software used at LAAS. You can find more details in Openrobots Wiki-Homepage
I-2. Robotpkg¶
Robotpkg 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).
I-3. GenoM¶
GenoM is a generator of modules, designed to be middleware independent, i.e. the same module can be compiled for, e.g., ROS, YARP, or Pocolibs, without any modification.
This allows a great code re-usability and to abstracts 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 have been provided.
Another specificity of GenoM is the interaction with and between components.
Each component is started independently 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, either with Matlab or TCL.
I-4. Pocolibs¶
Pocolibs is a middleware, like ROS.
It aims at being lighter 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 performance.
I-5. TeleKyb¶
The TeleKyb software platform provides the aerial-robotic oriented software developed at LAAS-CNRS.
In particular, we will use:
- pom, a UKF-based state estimator merging state feedback for different sources (e.g. mocap + IMU)
- optitrack, to export the motion capture data to the genom software stack
- rotorcraft, the low-level interface, with either the simulated or real platform
- maneuver, a global trajectory planner, providing position and attitude (as quaternions) as well as first and second derivatives. It implements take-off and waypoint-to-waypoint motions. A joystick-based velocity control is implemented, but not used in this project.
- dynamixel, an interface to control the Dynamixel motors. It is used since the gazebo gripper plugin used for the simulation (presented below) adopts the same interface protocol as the Dynamixel motors (precisely Dynamixel Protocol 2.0).
- joystick, a component to read the joystick inputs.
I-6. Gazebo¶
To simulate the platform, we use the Gazebo simulator. To interface it with the genom software stack, we use two dedicated components:
- mrsim-gazebo a plugin to interface the simulated multi-rotor with the genom components. It uses libmrsim, a Multi-Robot SIMulator interface, designed to be a transparent interface w.r.t. the real aerial vehicles used in LAAS-CNRS. It makes the transition between simulation and experiments transparent, from the software point of view.
- optitrack-gazebo emulates the optitrack network interface to publish the model poses.
The installation procedure for Gazebo can be found at http://www.gazebosim.org/tutorials?cat=install&tut=install_ubuntu&ver=9.0
I-7. TCL¶
The interaction with the GenoM components is handled using a scripting language, implementing the communication through the genomix HTTP server.
There are two available language interfaces: matlab and tcl.
eltclsh is an in-terminal TCL shell to interact with the components. However, in the following, we provide a TCL-based software that is all-embedded to avoid the use of the inline interaction through eltclsh.
II - Installation procedure¶
This section is a tutorial on how to install the software architecture to run the simulations.
II-0. Clone the Visual and Physical Control Architecture for Flying End-Effector repository¶
Clone the repo associated to this project, using the git daemon. Its root will act as the devel folder for the following.
git git://redmine.laas.fr/laas/visual-physical-control-architecture.git
cd ./visual-physical-control-architecture/
To simplify the installation, we provide a env.sh
script that exports all the required variables.
In order to run all the installed executables, we need to setup the path to the newly created folders.
/!\ the source has to be called in the repository root since it uses the pwd
command to export the paths.
source env.sh
II-1. Setup robotpkg¶
(Steps taken from http://robotpkg.openrobots.org/install.html)
1. Clone the robotpkg lastest release:¶
git clone git://git.openrobots.org/robots/robotpkg
2. Check that the openrobots/
folder exists in the repository root, and update the environement variables accordingly if you didn't source the env.sh
file:¶
export ROBOTPKG_BASE=`pwd`/openrobots
3. Install robotpkg¶
cd robotpkg/bootstrap
./bootstrap --prefix=$ROBOTPKG_BASE
4. Install the required components and their 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:
PKG_OPTIONS.%-genom3 = \
codels \
pocolibs-server \
pocolibs-client-c
PKGSET.mpcset = \
middleware/pocolibs \
architecture/genom3 \
architecture/genom3-pocolibs \
robots/rotorcraft-genom3 \
localization/pom-genom3 \
localization/optitrack-genom3 \
net/genomix \
supervision/tcl-genomix \
shell/eltclsh \
simulation/mrsim-gazebo \
simulation/libmrsim \
simulation/optitrack-gazebo \
hardware/dynamixel-genom3 \
joystick-genom3
PREFER.lapack = robotpkg
PREFIX.matlab = <path/to/Matlab>
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).
If Matlab is not installed on the system, remove the lines supervision/matlab-genomix \
and PREFIX.matlab = <path/to/Matlab>
from the above list.
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:
cd robotpkg
make update-mpcset
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.
II-2. Install custom components¶
List of the components¶
The
src/
folder contains some additional components, in particular:
- vision-idl: the type declaration regarding the camera modules
- camgazebo-genom3: read the data from the gazebo inate camera, via the gazebo API
- camviz-genom3: record and/or display the images from a camera
- arucotag-genom3: detect and filter (EKF-based) the ArUco markers/tags
- phynt-genom3: handle physical interaction (wrench observer and admittance filter)
- uavatt-genom3: attitude controler for fully-actuated UAVs
- uavpos-genom3: position controler for fully-actuated UAVs
- visualservoing-genom3: implement the state machine for the pick-n-place experiment and provide the reference trajectory (either based on visual-servoing, or based on waypoints for takeoff/exploration)
- libdynamixel: TODO
- magdynamixel-gazebo: TODO
Install the extra components¶
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, check that the devel folder exists, export the path if you didn't source the env.sh
. Then go to the sources folder:
export DEVEL_BASE=`pwd`/devel
cd src/
For the manual installation, asciidoctor
is needed. It can be installed using apt
or any package manager.
Each component here has to be installed manually, using autoconf
. To do so, proceed as follow:
cd src/<component>/
./bootstrap.sh
mkdir build
cd build
../configure --prefix=$DEVEL_BASE --with-templates=pocolibs/client/c,pocolibs/server
make install
The component vision-idl
has to be installed first since it defines some type headers used by others.
The installation of the main component, uavmpc-genom3
, is described in the next subection.
II-3. Setup the environment¶
In order to run all the installed executables, we need to setup the path to the newly created folders.
All the required variables are exported in the env.sh
file.
III - Running the simulation¶
The part is going to be filled soon.
III-1. GInterface¶
In order to start all the required softwares, connect the components together and store the parameters, we use a TCL-based interface.
The folder called ginterface contains all the necessary scripts.
For convenience, we provide as much generic scripts as possible.
The next section explains how to setup the ginterface, then how to use it to run the proposed simulation.
We also provide the "mission" script used in the experiment presented in the paper, so that the reader can have a glance to the parameters used in this experiment.
III-2. Setup the GInterface¶
III-3. Run the simulation¶
Updated by Gianluca Corsini over 3 years ago · 64 revisions