/pacnav

This repository contains the TMUX scripts to run the Gazebo simulations and real-world experiments for the paper entitled "PACNav: A Communication and External Localization Free Collective Swarm of UAVs"

Primary LanguageC++BSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

PACNav

This repository contains the scripts and code to run the Gazebo simulations and real-world experiments for the paper titled "PACNav: A Collective Navigation Approach for UAV Swarms Deprived of Communication and External Localization".

Step 1) Installation and building containers.

  • Install docker and singularity using the install scripts provided in pacnav/install directory. You may skip this if you already have these dependencies installed.
  • Build the singularity image by running ./singularity/recipe/build.sh.

Step 2) Running the container and building the ROS packages.

  • After a successful build, run the singularity container using ./singularity/run_singularity.sh script.
  • The script will mount the singularity/user_ros_workspace directory into the singularity container.
  • Build the required ROS packages by running catkin build -c inside singularity/user_ros_workspace.

Step 3) Running the mutli-UAV simulation.

  • After a successful catkin build, run the multi-UAV simulation using ./singularity/user_ros_workspace/src/mrs_swarm_core/simulation/simulate_swarm.sh -f config/sim_config.yaml
  • The parameters for setting up the multi-UAV simulation are in the singularity/user_ros_workspace/src/mrs_swarm_core/simulation/config/sim_config.yaml file. You can play around with them as you please.

Citation

Please use the citation below if you find our work useful 😊.

@acticle{Ahmad2022Bioinspired,
  title = {{PACNav: A collective navigation approach for UAV swarms deprived of communication and external localization}},
  author = {{Ahmad}, Afzal and {Bonilla Licea}, Daniel and {Silano}, Giuseppe and {Baca}, Tomas and {Saska}, Martin},
  doi = {10.1088/1748-3190/ac98e6},
  group = {journals},
  journal = {Bioinspiration & Biomimetics},
  year = {2022},
  organization = {IOP Science},
  month = oct,
  preprint = {http://mrs.felk.cvut.cz/data/papers/Bioinspired_Afzal.pdf},
  code = {https://github.com/ctu-mrs/pacnav},
  link = {https://iopscience.iop.org/article/10.1088/1748-3190/ac98e6}
}

YouTube video

In this section a video showcasing the validity and the effectviness of the approach is reported. Further videos can be found in the related publication.

PACNav: A collective navigation approach for UAV swarms deprived of communication and external localization