pacnav

KO | EN

gitlite — search

#javascript #python #hacktoberfest #react #ai #typescript #llm #go #golang #android #machine-learning #rust #deep-learning #linux

(★ 19)

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"

pacnav 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# 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 :blush:.

```bibtex
@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](https://github.com/ctu-mrs/pacnav/wiki/img/img_bio_22.png)](https://youtu.be/Cpuqx7Imrz4 "PACNav: A collective navigation approach for UAV swarms deprived of communication and external localization")

pacnav

pacnav 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

pacnav

pacnav 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README