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se2clam

SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision

Related Publication

  • Fan Zheng, Hengbo Tang, Yun-Hui Liu. "Odometry-Vision-Based Ground Vehicle Motion Estimation With SE(2)-Constrained SE(3) Poses". IEEE Transactions on Cybernetics, vol. 49, no. 7, 2019

    To cite it in bib:

    @article{fzheng2018tcyb,
      author  = {Fan Zheng and Hengbo Tang and Yun-Hui Liu},
      journal = {IEEE Trans. Cybernetics},
      title   = "{Odometry-Vision-Based Ground Vehicle Motion Estimation With SE(2)-Constrained SE(3) Poses}",
      volume  = {49},
      number  = {7},
      year    = {2019},
    }
    

Dependencies

  • ROS (tested on Kinetic/Melodic)

  • OpenCV 2.4.x / 3.1 above

  • g2o (2016 version)

Build

Build this project as a ROS package

Demo

  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 se2clam
    rosrun rviz rviz -d rviz.rviz
    
  4. Run se2clam:

    rosrun se2clam test_vn PATH_TO_DatasetRoom PATH_TO_ORBvoc.bin
    

    result in rviz

Related Project

izhengfan/se2lam
izhengfan/ORB_SLAM2

License

MIT

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SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)

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