OctoMap for Dynamic Points Removal in Maps

Author & Maintainer: Qingwen Zhang. Please give us a star if you like this repo! 🌟 and don't forget reference our DynamicMap benchmark for more detail on datasets, evaluation and comparison with other methods.

📜 ChangeLog:

• 2024/07/11: Remove as much as possible dependencies in this repo and update voxel-level clean map saved.
• 2023/07/03: Update all config including octomap, octomap w G, octomap w GF.
• 2023/04/05: Add dynamic points removal in octomap, and update the README.

0. Setup

System I tested: Ubuntu 18.04, 20.04.

Dependencies: PCL [Read and write Point Cloud], glog & gflag [Debug Printing]. Normally you may have PCL installed because of others like ROS/ROS2 etc.

sudo apt update && sudo apt install -y libpcl-dev 
sudo apt install -y libgoogle-glog-dev libgflags-dev

git clone this repo:

git clone https://github.com/Kin-Zhang/octomap

1. Build & RUN

Build Command:

cd octomap
cmake -B build && cmake --build build

Prepare demo data [KITTI sequence 00 only 384.8MB], or create your own data following these steps on Benchmark instruction:

wget https://zenodo.org/records/10886629/files/00.zip
unzip 00.zip -d ${data_path, e.g. /home/kin/data}

Run command:

./build/octomap_run /home/kin/data/00 assets/config_fg.toml -1

• -1 means all frames in the pcd folder, default is only 10 frame.

Demo result visualization in CloudCompare on demo data (KITTI sequence 00):

• left is raw map, and red points are dynamic points labeled by SemanticKITTI (ground truth).
• medium is octomap_fg point-level output.
• right is octomap_gf voxel-level output. Since some mapper may directly want downsampled map. Voxel resolution is based on the config you set in assets/config_fg.toml like: octomap/resolution=0.1 (10cm) and output/downsampled=true (voxel-level map).

2. Evaluation

Please reference to DynamicMap_Benchmark for the evaluation of this method and other dynamic removal methods.

Evaluation Section link

Acknowledgements & Cite

This implementation is based on codes from several repositories: octomapping, octomap. Thanks for their great work! ❤️

This work and the improved version is done during our DynamicMap benchmark. Please cite in following works if you use this code:

@inproceedings{zhang2023benchmark,
  author={Zhang, Qingwen and Duberg, Daniel and Geng, Ruoyu and Jia, Mingkai and Wang, Lujia and Jensfelt, Patric},
  booktitle={IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)}, 
  title={A Dynamic Points Removal Benchmark in Point Cloud Maps}, 
  year={2023},
  pages={608-614},
  doi={10.1109/ITSC57777.2023.10422094}
}

@article{hornung13auro,
  author = {Armin Hornung and Kai M. Wurm and Maren Bennewitz and Cyrill Stachniss and Wolfram Burgard},
  title = {{OctoMap}: An Efficient Probabilistic {3D} Mapping Framework Based on Octrees},
  journal = {Autonomous Robots},
  year = 2013,
  volume = 34,
  pages = {189-206},
  doi = {10.1007/s10514-012-9321-0},
}