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On-SE(2) Localization and Mapping for Ground Vehicles by Fusing Odometry and Vision

• Fan Zheng, Yun-Hui Liu. "Visual-Odometric Localization and Mapping for Ground Vehicles Using SE(2)-XYZ Constraints". Proc. IEEE International Conference on Robotics and Automation (ICRA), 2019 [pdf] [poster]

  To cite it in bib:

  @inproceedings{fzheng2019icra,
      author    = {Fan Zheng and Yun-Hui Liu},
      title     = "{Visual-Odometric Localization and Mapping for Ground Vehicles Using SE(2)-XYZ Constraints}",
      booktitle = {Proc. IEEE Int. Conf. Robot. Autom (ICRA)},
      year      = {2019},
  }
  

  

• ROS (tested on Kinetic/Melodic)

• OpenCV 2.4.x / 3.1 above

• g2o (2016 version)

Build this project as a ROS package

1. Download DatasetRoom.zip, and extract it. In a terminal, cd into DatasetRoom/.

   We prepare two packages of odometry measurement data, one is more accurate (odo_raw_accu.txt), the other less accurate (odo_raw_roug.txt). To use either one of them, copy it to odo_raw.txt in DatasetRoom/.

2. Download ORBvoc.bin.

3. Run rviz:

   roscd se2lam
   rosrun rviz rviz -d rviz.rviz
   

4. Run se2lam:

   rosrun se2lam test_vn PATH_TO_DatasetRoom PATH_TO_ORBvoc.bin
   

izhengfan/se2clam
izhengfan/ORB_SLAM2

MIT