MR_SLAM

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MR_SLAM

A modularized multi-robot SLAM system with elevation mapping and a costmap converter for easy navigation. Different odometry and loop closure algorithms can be easily integrated into the system.

View Demo · Report Bug · Request Feature

About The Project

This is a C++ library with ROS interface to manage multi-robot maps. It contains a pluggable front-end FAST-LIO2, a pluggable loop closure method DiSCO / RING. and a global manager that handles submaps, loop closure and back-end optimization. The optimizer is mainly based on GTSAM and dist-mapper. The system provides a 3D pointcloud map and a 2.5D elevation map output. The output elevation map can be easily converted to a costmap for navigation.

Author: Peter XU (Xuecheng XU)
Affiliation: ZJU-Robotics Lab
Maintainer: Peter XU, [email protected]

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Getting Started

Here, we provide an example to demonstrate the system. Some parameters can be changed to fit your needs.

Prerequisites

This software is built on the Robotic Operating System ([ROS]), which needs to be installed first. Additionally, the MR_SLAM depends on following software:

• Eigen (linear algebra library, tested on 3.2.9 & 3.3.4; failed on 3.3.9)

• CUDA (gpu process)

• GTSAM (pose optimization)

• Grid Map (grid map library for mobile robots)

  sudo apt install ros-$ROS_DISTRO-grid-map*
  

• OctoMap (octomap library for multi-resolution)

  sudo apt install ros-$ROS_DISTRO-octomap*
  

• Kindr

  Follow https://github.com/anybotics/kindr
  

• DiSCO (pluggable loop detector)

  Follow https://github.com/MaverickPeter/DiSCO-pytorch
  

• livox_ros_driver (for FAST_LIO2)

  Follow https://github.com/Livox-SDK/livox_ros_driver
  

• Fast GICP (for ICP refine)

  # Fast GICP is already include in the repo. You can use 
  git submodule sync
  git submodule init --recursive
  git submodule update
  
  # or you can clone the repo and put them in the same place
  Follow https://github.com/SMRT-AIST/fast_gicp
  

Installation

1. Clone the repo

   git clone https://github.com/MaverickPeter/MR_SLAM.git
   

2. Make Mapping

   cd Mapping && catkin_make
   

3. Make Localization

   cd Localization && catkin_make
   

4. Make LoopDetection

   cd LoopDetection && catkin_make
   
   # If you encounter the PyInit__tf2 issue, use catkin_make with your python3 environment
   catkin_make --cmake-args \
   -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=/home/client/miniconda3/envs/py3/bin/python3.8 \
   -DPYTHON_INCLUDE_DIR=/home/client/miniconda3/envs/py3/include/python3.8 \
   -DPYTHON_LIBRARY=/home/client/miniconda3/envs/py3/lib/libpython3.8.so
   

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Quick Demo

1. Get rosbag from Google Drive or Baidu Pan with extract code: gupx

2. Run roscore

3. Run bag

   rosbag play 3_dog.bag --clock --pause
   

4. Run DiSCO

   # !!!!! You need to change the Python interpreter to your environment The default is mine: #!/home/client/miniconda3/envs/disco/bin/python3
   
   cd LoopDetection && source devel/setup.bash
   rosrun disco_ros main.py 
   

5. Run global_manager

   cd Mapping && source devel/setup.bash
   roslaunch global_manager global_manager.launch
   

6. Visualization

   rviz -d Visualization/vis.rviz
   

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Full Usage

0. Run roscore

1. Run fast-lio (in 3 terminals)

   # Set parameters in Localization/src/FAST_LIO/launch/ and Localization/src/FAST_LIO/config/
   
   cd Localization && source devel/setup.bash
   roslaunch fast_lio robot_1.launch
   roslaunch fast_lio robot_2.launch
   roslaunch fast_lio robot_3.launch
   

2. Run elevation_mapping (in 3 terminals)

   # Set parameters in Mapping/src/elevation_mapping_periodical/elevation_mapping_demos/launch/ and Mapping/src/elevation_mapping_periodical/elevation_mapping_demos/config/
   
   cd Mapping && source devel/setup.bash
   roslaunch elevation_mapping_demos robot_1.launch
   roslaunch elevation_mapping_demos robot_2.launch
   roslaunch elevation_mapping_demos robot_3.launch   
   

3. Run DiSCO

   # You need to change the Python interpreter to your environment The default is mine: #!/home/client/miniconda3/envs/disco/bin/python3
   
   cd LoopDetection && source devel/setup.bash
   rosrun disco_ros main.py 
   

4. Run global_manager

   # Set parameters in Mapping/src/global_manager/launch/
   
   cd Mapping && source devel/setup.bash
   roslaunch global_manager global_manager.launch
   

5. Visualization

   rviz -d Visualization/vis.rviz
   

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Roadmap

• [ ] Optimize code.
• [ ] Add more pluggable loop closure methods.
• [ ] Support more front-end odometry.

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

Xuecheng Xu - [email protected]

Project Link: https://github.com/MaverickPeter/MR_SLAM

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