FAST-LIVO2 ROS2 HUMBLE

FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry

Thanks to hku mars lab chunran zheng for the open source excellent work

📢 News

• 🔓 2025-01-23: Code released!
• 🎉 2024-10-01: Accepted by T-RO '24!
• 🚀 2024-07-02: Conditionally accepted.

📬 Contact

If you have any questions, please feel free to contact: Chunran Zheng zhengcr@connect.hku.hk.

1. Introduction

FAST-LIVO2 is an efficient and accurate LiDAR-inertial-visual fusion localization and mapping system, demonstrating significant potential for real-time 3D reconstruction and onboard robotic localization in severely degraded environments.

1.1 Related video

Our accompanying video is now available on Bilibili and YouTube.

1.2 Related paper

FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry

FAST-LIVO: Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry

1.3 Our hard-synchronized equipment

We open-source our handheld device, including CAD files, synchronization scheme, STM32 source code, wiring instructions, and sensor ROS driver. Access these resources at this repository: LIV_handhold.

1.4 Our associate dataset: FAST-LIVO2-Dataset

Our associate dataset FAST-LIVO2-Dataset used for evaluation is also available online. Please note that the dataset is being uploaded gradually.

MARS-LVIG dataset

MARS-LVIG dataset：A multi-sensor aerial robots SLAM dataset for LiDAR-visual-inertial-GNSS fusion

2. Prerequisited

2.1 Ubuntu and ROS

Ubuntu 22.04. ROS Installation.

2.2 PCL && Eigen && OpenCV

PCL>=1.6, Follow PCL Installation.

Eigen>=3.3.4, Follow Eigen Installation.

OpenCV>=3.2, Follow Opencv Installation.

2.3 Sophus

Sophus Installation for the non-templated/double-only version.

git clone https://github.com/strasdat/Sophus.git
cd Sophus
git checkout a621ff
mkdir build && cd build && cmake ..
make
sudo make install

if build fails due to so2.cpp:32:26: error: lvalue required as left operand of assignment, modify the code as follows:

so2.cpp

namespace Sophus
{

SO2::SO2()
{
-  unit_complex_.real() = 1.;
-  unit_complex_.imag() = 0.;
+  unit_complex_.real(1.);
+  unit_complex_.imag(0.);
}

2.4 Vikit

Vikit contains camera models, some math and interpolation functions that we need. Vikit is a catkin project, therefore, download it into your catkin workspace source folder.

For well-known reasons, ROS2 does not have a direct global parameter server and a simple method to obtain the corresponding parameters. For details, please refer to https://discourse.ros.org/t/ros2-global-parameter-server-status/10114/11. I use a special way to get camera parameters in Vikit. While the method I've provided so far is quite simple and not perfect, it meets my needs. More contributions to improve rpg_vikit are hoped.

# Different from the one used in fast-livo1
cd fast_ws/src
git clone https://github.com/Robotic-Developer-Road/rpg_vikit.git 

Thanks to the following repositories for the code reference:

• uzh-rpg/rpg_vikit
• xuankuzcr/rpg_vikit
• uavfly/vikit

2.5 livox_ros_driver2

Follow livox_ros_driver2 Installation.

why not use livox_ros_driver? Because it is not compatible with ROS2 directly. actually i am not think there s any difference between livox ros driver and livox ros driver2 's CustomMsg, the latter 's ros2 version is sufficient.

3. Build

Clone the repository and colcon build:

cd ~/fast_ws/src
git clone https://github.com/Robotic-Developer-Road/FAST-LIVO2.git
cd ../
colcon build --symlink-install --continue-on-error
source ~/fast_ws/install/setup.bash

4. Run our examples

Download our collected rosbag files via OneDrive (FAST-LIVO2-Dataset).

convert rosbag

convert ROS1 rosbag to ROS2 rosbag

pip install rosbags
rosbags-convert --src Retail_Street.bag --dst Retail_Street

• gitlab rosbags
• pypi rosbags

change the msg type on rosbag

Such as dataset Retail_Street.db3, because we use livox_ros2_driver2's CustomMsg, we need to change the msg type in the rosbag file.

1. use rosbags-convert to convert rosbag from ROS1 to ROS2.
2. change the msg type of msg type in metadata.yaml as follows:

metadata.yaml

rosbag2_bagfile_information:
  compression_format: ''
  compression_mode: ''
  custom_data: {}
  duration:
    nanoseconds: 135470252209
  files:
  - duration:
      nanoseconds: 135470252209
    message_count: 30157
    path: Retail_Street.db3
    ..............
    topic_metadata:
      name: /livox/lidar
      offered_qos_profiles: ''
      serialization_format: cdr
-     type: livox_ros_driver/msg/CustomMsg
+     type: livox_ros_driver2/msg/CustomMsg
      type_description_hash: RIHS01_94041b4794f52c1d81def2989107fc898a62dacb7a39d5dbe80d4b55e538bf6d
    ...............
.....

Run the demo

Do not forget to source your ROS2 workspace before running the following command.

ros2 launch fast_livo mapping_aviz.launch.py use_rviz:=True
ros2 bag play -p Retail_Street  # space bar controls play/pause

5. License

The source code of this package is released under the GPLv2 license. For commercial use, please contact me at zhengcr@connect.hku.hk and Prof. Fu Zhang at fuzhang@hku.hk to discuss an alternative license.