Official page of Patchwork (RA-L'21 w/ IROS'21)

Overview

Patchwork

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

[Video] [Preprint Paper] [Project Wiki]

Patchwork Concept of our method (CZM & GLE)

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


Demo

KITTI 00

Rough Terrain


Characteristics

  • 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.

Contents

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

Test Env.

The code is tested successfully at

  • Linux 18.04 LTS
  • ROS Melodic

Requirements

ROS Setting

    1. Install ROS on a machine.
    1. 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
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
git clone https://github.com/LimHyungTae/patchwork.git
cd .. && catkin build patchwork 

How to Run Patchwork

We provide three examples

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

Offline KITTI dataset

  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
     |...
_____...
   
  1. Run launch file
roslaunch patchwork offline_kitti.launch

You can directly feel the speed of Patchwork! 😉

Online (ROS Callback) KITTI dataset

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
  1. After building this package, run the roslaunch as follows:
roslaunch patchwork rosbag_kitti.launch
  1. Then play the rosbag file in another command
rosbag play kitti_00_xyzilid.bag

Own dataset using pcd files

Please refer to /nodes/offilne_own_data.cpp.

(Note that in your own data format, there may not exist ground truth labels!)

Be sure to set right params. Otherwise, your results may be wrong as follows:

W/ wrong params After setting right params

For better understanding of the parameters of Patchwork, please read our wiki, 4. IMPORTANT: Setting Parameters of Patchwork in Your Own Env..

Offline (Using *.pcd or *.bin file)

  1. Utilize /nodes/offilne_own_data.cpp

  2. Please check the output by following command and corresponding files:

roslaunch patchwork offline_ouster128.launch

Online (via rosbag)

  1. Utilize rosbag_kitti.launch.

  2. To do so, remap the topic of subscriber, e.g. add remap line as follows:

<remap from="/node" to="$YOUR_LIDAR_TOPIC_NAME$"/>
  1. In addition, minor modification of ros_kitti.cpp is necessary by refering to offline_own_data.cpp.

Citation

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}
}

Description

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

Contact

If you have any questions, please let me know:

TODO List

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

Owner
Hyungtae Lim
Ph.D Candidate of URL lab. @ KAIST, South Korea
Hyungtae Lim
Implement A3C for Mujoco gym envs

pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A

Andrew 70 Dec 12, 2022
Python implementation of "Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation"

MIPNet: Multi-Instance Pose Networks This repository is the official pytorch python implementation of "Multi-Instance Pose Networks: Rethinking Top-Do

Rawal Khirodkar 57 Dec 12, 2022
A strongly-typed genetic programming framework for Python

monkeys "If an army of monkeys were strumming on typewriters they might write all the books in the British Museum." monkeys is a framework designed to

H. Chase Stevens 115 Nov 27, 2022
FwordCTF 2021 Infrastructure and Source code of Web/Bash challenges

FwordCTF 2021 You can find here the source code of the challenges I wrote (Web and Bash) in FwordCTF 2021 and the source code of the platform with our

Kahla 5 Nov 25, 2022
The easiest tool for extracting radiomics features and training ML models on them.

Simple pipeline for experimenting with radiomics features Installation git clone https://github.com/piotrekwoznicki/ClassyRadiomics.git cd classrad pi

Piotr Woźnicki 17 Aug 04, 2022
Implementation for Panoptic-PolarNet (CVPR 2021)

Panoptic-PolarNet This is the official implementation of Panoptic-PolarNet. [ArXiv paper] Introduction Panoptic-PolarNet is a fast and robust LiDAR po

Zixiang Zhou 126 Jan 01, 2023
ML models implementation practice

Let's implement various ML algorithms with numpy/tf Vanilla Neural Network https://towardsdatascience.com/lets-code-a-neural-network-in-plain-numpy-ae

Jinsoo Heo 4 Jul 04, 2021
A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image.

Minimal Body A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image. The model file is only 51.2 MB and runs a

Yuxiao Zhou 49 Dec 05, 2022
PyTorch implementation of CloudWalk's recent work DenseBody

densebody_pytorch PyTorch implementation of CloudWalk's recent paper DenseBody. Note: For most recent updates, please check out the dev branch. Update

Lingbo Yang 401 Nov 19, 2022
Global-Local Attention for Emotion Recognition

Global-Local Attention for Emotion Recognition Requirements Python 3 Install tensorflow (or tensorflow-gpu) = 2.0.0 Install some other packages pip i

Minh Nhat Le 15 Apr 21, 2022
Score refinement for confidence-based 3D multi-object tracking

Score refinement for confidence-based 3D multi-object tracking Our video gives a brief explanation of our Method. This is the official code for the pa

Cognitive Systems Research Group 47 Dec 26, 2022
Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training".

Mixup-Data-Dependency Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training". Running Alternating Line Exp

Muthu Chidambaram 0 Nov 11, 2021
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks

Adversarially-Robust-Periphery Code + Data from the paper "Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks" by A

Anne Harrington 2 Feb 07, 2022
Bio-OFC gym implementation and Gym-Fly environment

Bio-OFC gym implementation and Gym-Fly environment This repository includes the gym compatible implementation of the Bio-OFC algorithm from the paper

Siavash Golkar 1 Nov 16, 2021
Deep Image Matting implementation in PyTorch

Deep Image Matting Deep Image Matting paper implementation in PyTorch. Differences "fc6" is dropped. Indices pooling. "fc6" is clumpy, over 100 millio

Yang Liu 724 Dec 27, 2022
This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state.

This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state. Dependencies Account wi

Balamurugan Soundararaj 21 Dec 14, 2022
Blender Add-On for slicing meshes with planes

MeshSlicer Blender Add-On for slicing meshes with multiple overlapping planes at once. This is a simple Blender addon to slice a silmple mesh with mul

52 Dec 12, 2022
Code release for Local Light Field Fusion at SIGGRAPH 2019

Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion

1.1k Dec 27, 2022
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects

House-GAN++ Code and instructions for our paper: House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent

122 Dec 28, 2022
TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials

OrthNet TensorFlow, PyTorch and Numpy layers for generating multi-dimensional Orthogonal Polynomials 1. Installation 2. Usage 3. Polynomials 4. Base C

Chuan 29 May 25, 2022