Authors: David Tejero Ruiz & Miguel Gil Castilla
This project aims to model the interacton of UAVs by using artificial forces. This architecture allows to generate emergent swarm behaviours from simpler individual rules. Automatic formation of regular polyhedron, obstable avoidance, follow-the-leader algorithm implementation, etc.
This repository contains a python script to simulate the proposed forces testing different parameter settings in various scenarios.
This model has been tested in a simulation environment using Gazebo & ROS melodic and noetic & Ardupilot based on the tools provided by Intelligent-Quads and the Ardupilot's SITL model.
The used repositories have been forked and modified in order to implement a realistic 4-UAV swarm simulation using our force model.
- Ardupilot's SITL v4.3.1: Adapted to 4-UAV swarm instances
- IQ_SIM: Simulation Tools (only changed spawn angles in the file multi-drone.world)
- IQ_GNC: Guidance Navigation Control using our forces model.
To run our script and simulate the forces, simply run:
python3 fsm_uav.py
The required dependencies are Matplotlib, NumPy and Math.
Note that you can change de script to modify the environment, adding diferent obstacles, making the desired center of mass move, etc.
In home directory:
cd ~
sudo apt install git
git clone https://github.com/davidtr99/ardupilot/tree/Copter-4.3.1
cd ardupilot
git checkout Copter-4.3.1
git submodule update --init --recursive
sudo apt install python-matplotlib python-serial python-wxgtk3.0 python-wxtools python-lxml python-scipy python-opencv ccache gawk python-pip python-pexpect
sudo pip install future pymavlink MAVProxy
MAVProxy is a fully-functioning GCS for UAV’s. The intent is for a minimalist, portable and extendable GCS for any UAV supporting the MAVLink protocol (such as one using ArduPilot). For more information check out http://ardupilot.github.io/MAVProxy/html/index.html
Open ~/.bashrc for editing:
gedit ~/.bashrc
Add these lines to end of ~/.bashrc (the file open in the text editor):
export PATH=$PATH:$HOME/ardupilot/Tools/autotest
export PATH=/usr/lib/ccache:$PATH
Save and close the text editor.
Reload ~/.bashrc:
. ~/.bashrc
Run SITL (Software In The Loop) once to set params:
cd ~/ardupilot/ArduCopter
sim_vehicle.py -w
We use catkin build instead of catkin_make. Please install the following:
sudo apt-get install python-wstool python-rosinstall-generator python-catkin-tools
Then, initialize the catkin workspace:
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws
catkin init
Install the following ROS packages:
sudo apt install ros-<rosdistro>-mavros
sudo apt install ros-<rosdistro>-mavros-extras
or do it from source:
cd ~/catkin_ws
wstool init ~/catkin_ws/src
rosinstall_generator --upstream mavros | tee /tmp/mavros.rosinstall
rosinstall_generator mavlink | tee -a /tmp/mavros.rosinstall
wstool merge -t src /tmp/mavros.rosinstall
wstool update -t src
rosdep install --from-paths src --ignore-src --rosdistro `echo $ROS_DISTRO` -y
catkin build
Add a line to end of ~/.bashrc by running the following command:
echo "source ~/catkin_ws/devel/setup.bash" >> ~/.bashrc
update global variables
source ~/.bashrc
install geographiclib dependancy
sudo ~/catkin_ws/src/mavros/mavros/scripts/install_geographiclib_datasets.sh
Clone our fork:
cd ~/catkin_ws/src
git clone https://github.com/davidtr99/iq_sim
Our repository should now be copied to ~/catkin_ws/src/iq_sim/ (don't run this line. This is just saying that if you browse in the file manager, you will see those folders).
run the following to tell gazebo where to look for the iq models
echo "GAZEBO_MODEL_PATH=${GAZEBO_MODEL_PATH}:$HOME/catkin_ws/src/iq_sim/models" >> ~/.bashrc
Inside catkin_ws, run catkin build:
cd ~/catkin_ws
catkin build
update global variables
source ~/.bashrc
Simply clone our fork:
git clone https://github.com/davidtr99/iq_gnc
and build the workspace:
cd ~/catkin_ws/
catkin build
To demonstrate the functionalities you can try this:
At first go to your workspace and charge the enviroment variables:
cd ~/catkin_ws/
source devel/setup.bash
Then run the simulator:
roslaunch iq_sim multi_drone.launch
Open four new terminals and do the following:
# in all of them:
cd ~/ardupilot/ArduCopter/
# first terminal:
sim_vehicle.py -v ArduCopter -f gazebo-drone1 -I0
# second:
sim_vehicle.py -v ArduCopter -f gazebo-drone2 -I1
# third:
sim_vehicle.py -v ArduCopter -f gazebo-drone3 -I2
# forth:
sim_vehicle.py -v ArduCopter -f gazebo-drone4 -I3
The last commands will create four instances of the ardupilot SITL, which you will connect later to the simulation in gazebo.
Until you can see that each one is using the GPS, please do not continue with the tutorial.
...
All of them done? You are a beast, ok so we can keep going.
Open a new terminal (yes, another one we have two weeks to do this what do you want?) and enable the mavros instances:
roslaunch iq_sim multi-apm.launch
We have all the necessary tools to begin our experiments.
You can try these last commands to watch the algorithim working:
#new terminal
cd ~/catkin_ws/
roslaunch iq_gnc multi_spawn.launch
You will see the drones taking off and when they are holding a position in a concrete height, introduce the last command:
# last terminal, I promise
cd ~/catkin_ws/
rosrun iq_gnc fsm_dev.py
Now you can see the emerging behaviour caused by the force model algorithim.
