HD-CCSOM

HD-CCSOM: Hierarchical and Dense Collaborative Continuous Semantic Occupancy Mapping through Label Diffusion

This is a novel collaborative continuous semantic occupancy Mapping algorithm, opening up a new field of mapping.

Getting Started

Building with catkin

catkin_ws/src$ git clone https://github.com/BIT-DYN/HD-CCSOM
catkin_ws/src$ cd ..
catkin_ws$ catkin_make
catkin_ws$ source ~/catkin_ws/devel/setup.bash

Building using Intel C++ compiler (optional for better speed performance)

catkin_ws$ source /opt/intel/compilers_and_libraries/linux/bin/compilervars.sh intel64
catkin_ws$ catkin_make -DCMAKE_C_COMPILER=icc -DCMAKE_CXX_COMPILER=icpc
catkin_ws$ source ~/catkin_ws/devel/setup.bash

Downloading the Dataset

Download the demo dataset and place them in directory "catkin_ws/src/HD-CCSOM/data/*.bag".

Baidu Cloud Disk

Google Drive

Running the Demo

First, each robot builds a local semantic map.

catkin_ws$ roslaunch hd_ccsom multi_gazebo.launch

Then, you can run the command through the new terminal to complete the map sharing and fusion.

rosservice call /robot2/manual_triger

Each robot stores a local map and a global map.

Citation

@inproceedings{deng2022hd,
  title={Hd-ccsom: Hierarchical and dense collaborative continuous semantic occupancy mapping through label diffusion},
  author={Deng, Yinan and Wang, Meiling and Yang, Yi and Yue, Yufeng},
  booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={2417--2422},
  year={2022},
  organization={IEEE}
}