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decentralized_loam's Introduction

Decentralized_loam

A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs

Introduction

Decentralized_loam is the code implementation of our paper "A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs", which is developed based on our previous work Loam-livox. Our project fuses data from multiple LiDARs in a decentralized framework, which can not only address the problem of localization and mapping, but can also online calibrate the extrinsic of 6-DoF (includes 3-DoF of rotation and 3-DoF of translation).

(A). The bird's eye-view of the maps we reconstructed in one of our experiments. The point cloud data sampled from different LiDARs are rendered with different colors. (B). The satellite image of the experiment test ground; (C~E). The detailed inspection of the area marked in dashed circle in A.

Developer: Jiarong Lin

Our related paper: our paper is accepted to IROS 2020 and is now available on Arxiv:
A decentralized framework for simultaneous calibration, localization and mapping with multiple LiDARs

Our related video: our related videos are now available on YouTube (click below image to open):

video

1. Prerequisites

1.1 Ubuntu and ROS

Ubuntu 64-bit 16.04 or 18.04. ROS Kinetic or Melodic. ROS Installation and its additional ROS pacakge:

    sudo apt-get install ros-XXX-cv-bridge ros-XXX-tf ros-XXX-message-filters ros-XXX-image-transport

NOTICE: remember to replace "XXX" on above command as your ROS distributions, for example, if your use ROS-kinetic, the command should be:

    sudo apt-get install ros-kinetic-cv-bridge ros-kinetic-tf ros-kinetic-message-filters ros-kinetic-image-transport

1.2. Ceres Solver

Follow Ceres Installation.

1.3. PCL

Our code run abnormally with the lower version of PCL (version < PCL-1.9.0 ) due to some unknown reasons (maybe some bugs), therefore we recommend you install the latest version of PCL

cd YOUR_PATH
git clone https://github.com/PointCloudLibrary/pcl
cd pcl
mkdir build
cd build
cmake ..
sudo make install -j8

2. Build

Clone the repository and catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/hku-mars/decentralized_loam
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash

3. Run our example

Download Our recorded rosbag and then

roslaunch dc_loam demo.launch
rosbag play dc_loam_demo.bag

Our hardware design

Not only our codes and algorithms are of open-source, but also our hardware design. You can visit this project (https://github.com/hku-mars/lidar_car_platfrom) for more details :)

License

The source code is released under GPLv2 license.

We are still working on improving the performance and reliability of our codes. For any technical issues, please contact me via email Jiarong Lin < [email protected] >.

For commercial use, please contact Dr. Fu Zhang < [email protected] >

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decentralized_loam's Issues

How to save the entire map?

Hi,
I'd like to know how to save the entire map to pcd file instead of just saving pcd files of every frame?

The dataset can not be get

I wanted to do some experiments with the dataset mentioned in this article. However, I was unable to download these datasets via the website link given in the article. I would appreciate it if you could share the dataset with me.

Does it adapt to high speed?

Hello, I'm really interested in your project, and looking forward to the release!
I am curious about whether this SLAM framework is robust in high speed scenario, i.e. 50~80km/h ? Or it is designed only for low speed vehicles?

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