Skip to content

Open-source code for the RA-L paper "Star-Searcher: An Efficient Aerial System for Target Search in Unknown Environments".

Notifications You must be signed in to change notification settings

SYSU-STAR/STAR-Searcher

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 

Repository files navigation

STAR-Searcher

Yiming Luo , Zixuan Zhuang, Neng Pan, Chen Feng, Shaojie Shen, Fei Gao, Hui Cheng and Boyu Zhou.

IEEE Robotics and Automation Letters (RA-L 2024)

This repository contains the codebase and associated resources for our paper titled "Star-Searcher: An Efficient Aerial System for Target Search in Unknown Environments ". This work tackles the challenge of autonomous target search using unmanned aerial vehicles (UAVs) in complex unknown environments.

The project involves novel algorithms for:

  • Visibility-based viewpoint clustering , allows the real-time generation of the global path at the level of viewpoint clusters and local path at the level of individual viewpoints with fewer detours.
  • History-aware path planning, which utilizes historical path information to prevent inconsistency in consecutive planning processes.
  • Other useful tools for autonomous search tasks.

Video links on Youtube and Bilibili. Please kindly star ⭐ this project if it helps you.

Quick Start

The project has been tested on Ubuntu 20.04(ROS Noetic) and 18.04(ROS Melodic). Take Ubuntu 20.04 as an example, run the following commands to setup:

  sudo apt-get install libnlopt-dev
  cd ${YOUR_WORKSPACE_PATH}/src
  git clone [email protected]:SYSU-STAR/STAR-Searcher.git
  cd ../ 
  catkin_make

After the compilation you can start the simulation environments by:

source devel/setup.bash && roslaunch exploration_manager env_simulation.launch

the simulation world filename is also specified in this launch file. After loading the world, run the uav simulation by:

source devel/setup.bash && roslaunch exploration_manager uav_simulation.launch

Then you can run the simulation and visualization by:

source devel/setup.bash && roslaunch exploration_manager rviz.launch 2> >(grep -v TF_REPEATED_DATA )
source devel/setup.bash && roslaunch exploration_manager search_map1.launch 2> >(grep -v TF_REPEATED_DATA )

You will find the local map and frontiers in the rviz and use the 2D Nav Goal to send the begin message.

Known Issues

  • If you encounter compilation errors about nlopt, like"No such file nlopt.hpp", please install nlopt manually (refer to this document).

Citation

@article{Luo_2024,
   title={Star-Searcher: A Complete and Efficient Aerial System for Autonomous Target Search in Complex Unknown Environments},
   volume={9},
   ISSN={2377-3774},
   url={http://dx.doi.org/10.1109/LRA.2024.3379840},
   DOI={10.1109/lra.2024.3379840},
   number={5},
   journal={IEEE Robotics and Automation Letters},
   publisher={Institute of Electrical and Electronics Engineers (IEEE)},
   author={Luo, Yiming and Zhuang, Zixuan and Pan, Neng and Feng, Chen and Shen, Shaojie and Gao, Fei and Cheng, Hui and Zhou, Boyu},
   year={2024},
   month=may, pages={4329–4336} }

About

Open-source code for the RA-L paper "Star-Searcher: An Efficient Aerial System for Target Search in Unknown Environments".

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published