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IMPORTANT: (Aug. 18th, 2024) I employ TBB, so its FPS is increased from 50 Hz to 100 Hz! If you want to use the paper version of Patchwork for SOTA comparison purpose, Please use this ground seg. benchmark code.
| Patchwork | Concept of our method (CZM & GLE) |
|---|---|
 |
 |
It's an overall updated version of R-GPF of ERASOR [Code] [Paper].
The code is tested successfully at
- Linux 24.04 LTS
- ROS2 Jazzy
ROS Noetic version can be found here
mkdir -p ~/colcon/src
cd ~/colcon/src
git clone https://github.com/LimHyungTae/patchwork.git
cd ..
colcon build --packages-up-to patchwork --cmake-args -DCMAKE_BUILD_TYPE=Release-
Download SemanticKITTI Odometry dataset (We also need labels since we also open the evaluation code! :)
-
The
dataset_pathshould consist ofvelodynefolder andlabelsfolder as follows:
data_path (e.g. 00, 01, ..., or 10)
_____velodyne
|___000000.bin
|___000001.bin
|___000002.bin
|...
_____labels
|___000000.label
|___000001.label
|___000002.label
|...
_____...
- Run launch file
ros2 launch patchwork evaluate.launch.yaml evaluate_semantickitti:=true dataset_path:=<YOUR_TARGET_SEQUENCE_DIR>"
e.g.,
ros2 launch patchwork evaluate.launch.yaml evaluate_semantickitti:=true dataset_path:="/home/hyungtae_lim/semkitti/dataset/sequences/04"
ros2 launch patchwork run_patchwork.launch.yaml scan_topic:=<YOUR_TOPIC_NAME> sensor_type:=<YOUR_SENSOR_TYPE>
e.g.,
ros2 launch patchwork run_patchwork.launch.yaml scan_topic:="/acl_jackal2/lidar_points" sensor_type:="velodyne16"
For better understanding of the parameters of Patchwork, please read our wiki, 4. IMPORTANT: Setting Parameters of Patchwork in Your Own Env..
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}
}
- Merry christmas eve XD!
include/label_generatoris added to make the.labelfile, following the SemanticKITTI format. - The
.labelfiles can be directly used in 3DUIS benchmark - Thank Lucas Nunes and Xieyuanli Chen for providing code snippets to save a
.labelfile.
- Pybinding + more advanced version is now available on Patchwork++ as a preprocessing step for deep learning users (i.e., python users can also use our robust ground segmentation)!
- For increasing convenience of use, the examples and codes are extensively revised by reflecting issue #12.
- The meaning of
elevation_thresholdsis changed to increase the usability. The meaning is explained in wiki. - A novel height estimator, called All-Terrain Automatic heighT estimator (ATAT) is added within the patchwork code, which auto-calibrates the sensor height using the ground points in the vicinity of the vehicle/mobile robot.
- Please refer to the function
consensus_set_based_height_estimation().
- Please refer to the function