/semantic-histogram-based-global-localization

Semantic graph based global localization for multi-robot map fusion.

Primary LanguageC++MIT LicenseMIT

Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment

Related Publications:

Xiyue Guo, Junjie Hu, Junfeng Chen, Fuqin Deng, Tin Lun Lam, Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment, IEEE Robotics and Automation Letters, 2021. PDF.

ORB-SLAM3

Results

1. Prerequisites

  • Ubuntu
  • CMake
  • Eigen
  • Pangolin
  • OpenCV
  • PCL (version below 1.10)

2. Running

Clone the repository and catkin_make:

    git clone https://https://github.com/gxytcrc/Semantic-Graph-based--global-Localization.git
    mkdir build
    cd build
    cmake ..
    make -j8

Download the dataset that is created from Airsim, and save them into the Datset . Download link: https://drive.google.com/file/d/106sPA48vFThLK0RB4WBcj-i8FZPQPmcV/view?usp=sharing.

Launch it as follows:

./mapAlignment robot1-foldername startFrameNumber endFrameNumber robot2-foldername startFrameNumber endFrameNumber

Citation

@inproceedings{XiyueGuo2021,
title={Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment},
author={Xiyue Guo, Junjie Hu, Junfeng Chen, Fuqin Deng, Tin Lun Lam},
booktitle=IEEE Robotics and Automation Letters (RA-L)},
year={2021}
}