SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision
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},
}
ROS (tested on Kinetic/Melodic)
OpenCV 2.4.x / 3.1 above
g2o (2016 version)
Build this project as a ROS package
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/
.
Download ORBvoc.bin.
Run rviz:
roscd se2clam
rosrun rviz rviz -d rviz.rviz
Run se2clam:
rosrun se2clam test_vn PATH_TO_DatasetRoom PATH_TO_ORBvoc.bin
izhengfan/se2lam
izhengfan/ORB_SLAM2