Official page of "Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor", which is accepted by RA-L with IROS'21 option

Patchwork	Concept of our method (CZM & GLE)

It's an overall updated version of R-GPF of ERASOR [Code] [Paper].

• Single hpp file (include/patchwork/patchwork.hpp)

• Robust ground consistency

As shown in the demo videos and below figure, our method shows the most promising robust performance compared with other state-of-the-art methods, especially, our method focuses on the little perturbation of precision/recall as shown in this figure.

Please kindly note that the concept of traversable area and ground is quite different! Please refer to our paper.

0. Test Env.
1. Requirements
2. How to Run Patchwork
3. Citation

The code is tested successfully at

• Linux 18.04 LTS
• ROS Melodic

• 1. Install ROS on a machine.
• 2. Thereafter, jsk-visualization is required to visualize Ground Likelihood Estimation status.

sudo apt-get install ros-melodic-jsk-recognition
sudo apt-get install ros-melodic-jsk-common-msgs
sudo apt-get install ros-melodic-jsk-rviz-plugins

• 3. Compile compile this package. We use catkin tools,

mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
git clone https://github.com/LimHyungTae/patchwork.git
cd .. && catkin build patchwork 

We provide three examples

• Offline KITTI dataset
• Online (ROS Callback) KITTI dataset
• Own dataset using pcd files

1. Download SemanticKITTI Odometry dataset (We also need labels since we also open the evaluation code! :)

2. Set the data_path in launch/offline_kitti.launch for your machine.

The data_path consists of velodyne folder and labels folder as follows:

data_path (e.g. 00, 01, ..., or 10)
_____velodyne
     |___000000.bin
     |___000001.bin
     |___000002.bin
     |...
_____labels
     |___000000.label
     |___000001.label
     |___000002.label
     |...
_____...
   

3. Run launch file

roslaunch patchwork offline_kitti.launch

You can directly feel the speed of Patchwork! 😉

We also provide rosbag example. If you run our patchwork via rosbag, please refer to this example.

1. Download readymade rosbag

wget https://urserver.kaist.ac.kr/publicdata/patchwork/kitti_00_xyzilid.bag

2. After building this package, run the roslaunch as follows:

roslaunch patchwork rosbag_kitti.launch

3. Then play the rosbag file in another command

rosbag play kitti_00_xyzilid.bag

To be updated (In fact, we already set the data loader in include/tools/pcd_loader.hpp)

If you use our code or method in your work, please consider citing the following:

@article{lim2021patchwork,
title={Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor},
author={Lim, Hyungtae and Minho, Oh and Myung, Hyun},
journal={IEEE Robotics and Automation Letters},
year={2021}
}

All explanations of parameters and other experimental results will be uploaded in wiki

If you have any questions, please let me know:

• Hyungtae Lim {[email protected]}

• Add ROS support
• Add preprint paper
• Add demo videos
• Add demo examples
• Update wiki