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
This is an implementation of PIFuhd based on Pytorch

Open-PIFuhd This is a unofficial implementation of PIFuhd PIFuHD: Multi-Level Pixel-Aligned Implicit Function forHigh-Resolution 3D Human Digitization

Lingteng Qiu 235 Dec 19, 2022
Matching python environment code for Lux AI 2021 Kaggle competition, and a gym interface for RL models.

Lux AI 2021 python game engine and gym This is a replica of the Lux AI 2021 game ported directly over to python. It also sets up a classic Reinforceme

Geoff McDonald 74 Nov 03, 2022
GAN-based Matrix Factorization for Recommender Systems

GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res

Ervin Dervishaj 9 Nov 06, 2022
Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

A Critical Assessment of State-of-the-Art in Entity Alignment This repository contains the source code for the paper A Critical Assessment of State-of

Max Berrendorf 16 Oct 14, 2022
JORLDY an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise

Repository for Open Source Reinforcement Learning Framework JORLDY

Kakao Enterprise Corp. 330 Dec 30, 2022
Code for "Retrieving Black-box Optimal Images from External Databases" (WSDM 2022)

Retrieving Black-box Optimal Images from External Databases (WSDM 2022) We propose how a user retreives an optimal image from external databases of we

joisino 5 Apr 13, 2022
Public scripts, services, and configuration for running a smart home K3S network cluster

makerhouse_network Public scripts, services, and configuration for running MakerHouse's home network. This network supports: TODO features here For mo

Scott Martin 1 Jan 15, 2022
Problem-943.-ACMP - Problem 943. ACMP

Problem-943.-ACMP В "main.py" расположен вариант моего решения задачи 943 с серв

Konstantin Dyomshin 2 Aug 19, 2022
Vehicle speed detection with python

Vehicle-speed-detection In the project simulate the tracker.py first then simulate the SpeedDetector.py. Finally, a new window pops up and the output

3 Dec 15, 2022
Implementation of Heterogeneous Graph Attention Network

HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19

5 Dec 28, 2021
Banglore House Prediction Using Flask Server (Python)

Banglore House Prediction Using Flask Server (Python) 🌐 Links 🌐 📂 Repo In this repository, I've implemented a Machine Learning-based Bangalore Hous

Dhyan Shah 1 Jan 24, 2022
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data

FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well i

0 Sep 06, 2022
The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22

SiamTPN Introduction This is the official implementation of the SiamTPN (WACV2022). The tracker intergrates pyramid feature network and transformer in

Robotics and Intelligent Systems Control @ NYUAD 28 Nov 25, 2022
RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection

RODD Official Implementation of 2022 CVPRW Paper RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection Introduction: Recent studie

Umar Khalid 17 Oct 11, 2022
Flower - A Friendly Federated Learning Framework

Flower - A Friendly Federated Learning Framework Flower (flwr) is a framework for building federated learning systems. The design of Flower is based o

Adap 1.8k Jan 01, 2023
This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

MPDL---TODO This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch. Ci

CodebaseLi 3 Nov 27, 2022
It is a system used to detect bone fractures. using techniques deep learning and image processing

MohammedHussiengadalla-Intelligent-Classification-System-for-Bone-Fractures It is a system used to detect bone fractures. using techniques deep learni

Mohammed Hussien 7 Nov 11, 2022
Compute descriptors for 3D point cloud registration using a multi scale sparse voxel architecture

MS-SVConv : 3D Point Cloud Registration with Multi-Scale Architecture and Self-supervised Fine-tuning Compute features for 3D point cloud registration

42 Jul 25, 2022
Collection of common code that's shared among different research projects in FAIR computer vision team.

fvcore fvcore is a light-weight core library that provides the most common and essential functionality shared in various computer vision frameworks de

Meta Research 1.5k Jan 07, 2023
DP-CL(Continual Learning with Differential Privacy)

DP-CL(Continual Learning with Differential Privacy) This is the official implementation of the Continual Learning with Differential Privacy. If you us

Phung Lai 3 Nov 04, 2022