Git Product home page Git Product logo

d-liom's Introduction

D-LIOM: Tightly-coupled Direct LiDAR-Inertial Odometry and Mapping

Our paper: we have corrected some typos and errors in Section III-D of the previous version of the paper, the revised version can be accessed here. When amending our paper, I would like to say thanks to Sky Shaw, who has found my errors and warmly provided his suggestions.

Related video: A running demo can be found at https://youtu.be/21J2QLUQbno or at https://www.bilibili.com/video/BV14y4y157du.


Sensor suite supported

  • 6-axis IMU + Velodyne/Ouster/Robosense LiDAR (Livox LiDAR can be also supported if the data of which is tansformed to the format of velodyne's, i.e., PointXYZRT.)

Prerequisites


Build

  • Clone this repository in your ROS workspace

  • Set CMake variable "OpenCV_DIR" in the root CMakeLists.txt of "cartographer".

  • Return to the root folder of your ROS workspace (which has the same directory as this "README" file) and run:

    catkin_make_isolated
    

Run an online demo

TONGJI Dataset

  • Some demo sequences can be downloaded via:

    • TONGJI dataset: link, pwd: hfrl
  • roslaunch dlio demo_dlio_tongji.launch bag_filename:=BAG_FILE_PATH where BAG_FILE_PATH is the full path of the downloaded bag file in your device

  • Some results on the self-collected TONGJI dataset.

NTU-VIRAL

  • The dataset is available online at NTU-VIRAL

  • ```roslaunch dlio demo_dlio_viral.launch bag_filename:=BAG_FILE_PATH```
    

    where BAG_FILE_PATH is the full path of the downloaded bag file in your device

  • Results on VIRAL
    

KAIST-Complex Urban Dataset

  • The dataset is available online at KAIST

  • Play KAIST bag follow the instruction: file_player

  • roslaunch dlio demo_dlio_kaist.launch

  • Results on KAIST "Urban-09" and "Urban-10"

Your own data

  • Write a urdf file of your device and save it to folder 'urdf'
  • Write a configuration file of your data and save it to 'config'
  • Write a launch file of your data and save it to 'launch'
  • Run your bag as above examples

Run offline and view mapping result

Launch dlio offline

roslaunch dlio dlio_offline_tongji bag_filenames:=BAG_FILE_PATH

View mapping result

roslaunch dlio dlio_map_viewer_rectified urdf_filename:=tongji pose_graph_pb_filename:=PG_FILENAME range_data_pb_filename:=RD_FILENAME rate:=100

where PG_FILENAME and RD_FILENAME are binary pbstream files saved to disk when launch the offline script above.


Acknowledgements

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.