This repository adapts the state-of-the-art lidar inertial odometry algorithm, Point-LIO
, for use with our lidar products:
Unitree LiDAR L1
Unitree LiDAR L2
Both L1
and L2
possess these features:
- large field of view (360° × 90°)
- non-repetitive scanning
- low cost
- suitable for applications in low-speed mobile robots
If you want to learn more about our lidar products, you can refer to the official website for details.
Point-LIO
is a robust and high-bandwidth lidar inertial odometry (LIO) with the capability to provide accurate, high-frequency odometry and reliable mapping under severe vibrations and aggressive motions. If you need further information about the Point-LIO
algorithm, you can refer to their official website and paper:
- https://github.com/hku-mars/Point-LIO
- Point‐LIO: Robust High‐Bandwidth Light Detection and Ranging Inertial Odometry
We tested our code on Ubuntu20.04 with ROS noetic. Ubuntu18.04 and lower versions have problems of environments to support the Point-LIO, try to avoid using Point-LIO in those systems.
You can refer to the official website to install ROS noetic:
Additional ROS package is required:
sudo apt-get install ros-xxx-pcl-conversions
Following the official Eigen installation, or directly install Eigen by:
sudo apt-get install libeigen3-dev
For using lidar L1
, you should download and build unilidar_sdk follwing these steps:
git clone https://github.com/unitreerobotics/unilidar_sdk.git
cd unilidar_sdk/unitree_lidar_ros
catkin_make
For using lidar L2
, you should download and build unilidar_sdk2 follwing these steps:
git clone https://github.com/unitreerobotics/unilidar_sdk2.git
cd unilidar_sdk/unitree_lidar_ros
catkin_make
Clone this repository and run catkin_make
:
mkdir -p catkin_point_lio_unilidar/src
cd catkin_point_lio_unilidar/src
git clone https://github.com/unitreerobotics/point_lio_unilidar.git
cd ..
catkin_make
To ensure proper initialization of the IMU, it is advisable to keep the lidar in a stationary state during the initial few seconds of algorithm execution.
Run unilidar
:
cd unilidar_sdk/unitree_lidar_ros
source devel/setup.bash
roslaunch unitree_lidar_ros run_without_rviz.launch
Run Point-LIO
:
cd catkin_unilidar_point_lio
source devel/setup.bash
roslaunch point_lio_unilidar mapping_unilidar_l1.launch
After completion of the run, all cached pointcloud map will be saved to the following path:
catkin_point_lio_unilidar/src/point_lio_unilidar/PCD/scans.pcd
You can use the pcl_viewer
tool to view this pcd file:
pcl_viewer scans.pcd
If you don't have our lidar for now, you can download our dataset recorded with our lidar and run testify this algorithm with it. The download address is here:
Run Point-LIO
:
cd catkin_point_lio_unilidar
source devel/setup.bash
roslaunch point_lio_unilidar mapping_unilidar_l1.launch
Play the dataset you downloaded:
rosbag play unilidar-2023-09-22-12-42-04.bag
After completion of the run, all cached pointcloud map will be saved to the following path:
catkin_point_lio_unilidar/src/point_lio_unilidarPCD/scans.pcd
You can use the pcl_viewer
tool to view this pcd file:
pcl_viewer scans.pcd
To ensure proper initialization of the IMU, it is advisable to keep the lidar in a stationary state during the initial few seconds of algorithm execution.
Run unilidar
:
cd unilidar_sdk/unitree_lidar_ros
source devel/setup.bash
roslaunch unitree_lidar_ros run_without_rviz.launch
Run Point-LIO
:
cd catkin_unilidar_point_lio
source devel/setup.bash
roslaunch point_lio_unilidar mapping_unilidar_l2.launch
After completion of the run, all cached pointcloud map will be saved to the following path:
catkin_point_lio_unilidar/src/point_lio_unilidar/PCD/scans.pcd
You can use the pcl_viewer
tool to view this pcd file:
pcl_viewer scans.pcd
If you don't have our lidar for now, you can download our dataset recorded with our lidar and run testify this algorithm with it. The download address is here:
Run Point-LIO
:
cd catkin_point_lio_unilidar
source devel/setup.bash
roslaunch point_lio_unilidar mapping_unilidar_l2.launch
Play the dataset you downloaded:
rosbag play XXXXXX.bag
After completion of the run, all cached pointcloud map will be saved to the following path:
catkin_point_lio_unilidar/src/point_lio_unilidarPCD/scans.pcd
You can use the pcl_viewer
tool to view this pcd file:
pcl_viewer scans.pcd