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https://github.com/izhengfan/se2clam
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
https://github.com/izhengfan/se2clam
g2o graph-optimization robotics ros slam state-estimation visual-slam
Last synced: 27 days ago
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SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
- Host: GitHub
- URL: https://github.com/izhengfan/se2clam
- Owner: izhengfan
- License: mit
- Created: 2019-03-04T07:55:28.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-05-10T02:26:28.000Z (about 4 years ago)
- Last Synced: 2024-02-10T05:36:57.877Z (4 months ago)
- Topics: g2o, graph-optimization, robotics, ros, slam, state-estimation, visual-slam
- Language: C++
- Homepage: https://github.com/izhengfan/se2clam
- Size: 137 KB
- Stars: 158
- Watchers: 9
- Forks: 55
- Open Issues: 3
-
Metadata Files:
- Readme: README.MD
- License: LICENSE
Lists
- Awesome-SLAM - se2clam - Constrained Localization and Mapping by Fusing Odometry and Vision (2. Visual SLAM / 2.5 Others)
README
se2clam
---
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision
[](../../actions?query=workflow%3A"Build")
### 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](https://github.com/RainerKuemmerle/g2o/releases/tag/20160424_git))
### Build
Build this project as a ROS package
### Demo
1. Download [DatasetRoom.zip](https://mycuhk-my.sharepoint.com/:u:/g/personal/1155051778_link_cuhk_edu_hk/Ef4NuXvLZI1JhfljH9LkNxUB5xrDrCOrRnxwztO5bGKlew?e=U4aind), 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](https://mycuhk-my.sharepoint.com/:u:/g/personal/1155051778_link_cuhk_edu_hk/EaF2ZkP17rdJrUHT0mrcf74Bl1h_691xZrxNILGbQbYFmA?e=nXRSS4).
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
```
### Related Project
[izhengfan/se2lam](https://github.com/izhengfan/se2lam)
[izhengfan/ORB_SLAM2](https://github.com/izhengfan/ORB_SLAM2)
### License
[MIT](LICENSE)