benchun123 / object-based-loop-closure

Object-based Loop Closure with Directional Histogram Descriptor

Related Paper:

• Benchun Zhou, Yongqi Meng, Furmans Kai. Object-based Loop Closure with Directional Histogram Descriptor[C]//2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). IEEE, 2022.: 1346-1351. [Link] [PDF] [Slide] [Youtube] [Bilibili]

• If you use the code in your academic work, please cite the above paper.

1. Prerequisites

• Ubuntu (18.04.5)
• CMake (3.10.2)
• Eigen (3)
• OpenCV (3.2.0)
• PCL (1.8.1)
• Note: the code builds on the top of ORB-SLAM2, if you meet compile problems, please refer to ORB-SLAM2.

2. Running

Clone the repository and catkin_make:

    git clone https://github.com/benchun123/object-based-loop-closure.git
    cd object-based-loop-closure
    sh build.sh

Launch it as follows:

    ./mono_ustc ~/path/to/dataset

3. Dataset

the open-source code runs on a USTC Sequence of USTC RGB-D Dataset(password:epya), we only unzip 2020-11-13-15-41-05, other six sequence are not explored.

4. Note

The main contribution of the code is to add a function DetectObjectLoop() in "LoopClosing.cc" to detect object loop, once the loop is detected, we use CorrectObjectLoop() to close the loop.

please check "LoopClosing.h" and "LocalMapping.h" for more details.

5. Acknowledgement

Thanks for the great work: Topology Loop Closure, ORB-SLAM2, Cube SLAM, and EAO-SLAM

• Lin, S., Wang, J., et al. Topology aware object-level semantic mapping towards more robust loop closure[J]. IEEE Robotics and Automation Letters, 2021: 7041-7048. [PDF].
• Mur-Artal R, Tardós J D. Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras[J]. IEEE Transactions on Robotics, 2017, 33(5): 1255-1262. [PDF], [Code]
• Yang S, Scherer S. Cubeslam: Monocular 3-d object slam[J]. IEEE Transactions on Robotics, 2019, 35(4): 925-938. [PDF], [Code]
• Wu, Y., Zhang, Y., et al. Eao-slam: Monocular semi-dense object slam based on ensemble data association[C].//In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4966-4973. IEEE, 2020. [PDF] [Code]

6. Description