A ros package for robust odometry and mapping using LiDAR with aid of different sensors

Related tags

Miscellaneous W-LOAM
Overview

W-LOAM

A ros package for robust odometry and mapping using LiDAR with aid of different sensors

Demo Video

https://www.bilibili.com/video/BV1Fy4y1L7kZ?from=search&seid=6228704901331074158&spm_id_from=333.337.0.0

Sensor Configure

  1. wheel encoder + steer encoder + LiDAR
    This is proposed by this repo
  2. IMU + LiDAR
    The imuOdometry is implemented based on
    https://github.com/TixiaoShan/LIO-SAM/blob/master/src/imuPreintegration.cpp
  3. configure 1 or 2 + GPS
    For mapping a large area, GPS is favored

Dependency

  • ROS (tested with melodic)
    sudo apt install ros-melodic-gps-common
    # optional
    # if you want to visualize with satellite maps, use rviz plugin rviz_satellite
    cd YOUR_CATKIN_WS/src
    git clone https://github.com/Saki-Chen/rviz_satellite
    cd .. && catkin_make -DCMAKE_BUILD_TYPE=Release
  • gtsam (tested with 4.0.3)
    refer to https://github.com/borglab/gtsam
    or for ubuntu 18.04
    git clone https://github.com/borglab/gtsam
    cd gtsam
    git checkout 4.0.3
    mkdir build && cd build
    cmake ..
    make -j8
    sudo make install

Build

cd YOUR_CATKIN_WS/src
git clone https://github.com/Saki-Chen/apa_msgs
git clone https://github.com/Saki-Chen/W-LOAM
cd .. && catkin_make -DCMAKE_BUILD_TYPE=Release

Data Format

  1. Point
    float32 x   
    float32 y      
    float32 z    
    float32 intensity
    // id of the laser scaner
    uint16 ring
    // time relative to the header stamp  
    float32 rel_time    
  1. Wheel Counting
    std_msgs/Header header
    // four counter for four wheel
    int64 FL
    int64 FR
    int64 RL
    int64 RR
  1. Steer Angle
    std_msgs/Header header
    // positive for clock-wise
    float64 angle
  1. IMU (sensor_msgs/Imu )

Calibration

The extrinsic for sensors is expressed as urdf file in folder launch/config.
Especially, the parameter file for Wheel Odometry is in vehicle_params.

Run

  1. using provided test bag
1. Download bag
https://pan.baidu.com/s/1v_jl-j4jdTZGjtW3P6c7Eg   
password: nk5a

2. run algorithm
// with wheel odometry
roslaunch wloam run.launch simulation:=true
// or with imu odometry
roslaunch wloam run.launch simulation:=true odometry_link:=imu_link

3. run rviz
roslaunch wloam rviz.launch

4. play bag
rosbag play parking-lot.bag --clock
  1. using dataset provided by lio-sam
goto https://github.com/TixiaoShan/LIO-SAM
1. Find and Download bag
Walking, Park and Garden is tested

2. run algorithm
roslaunch wloam run.launch laser_topic:=points_raw imu_topic:=imu_raw cloud_format:=velodyne robot_name:=lio odometry_link:=imu_link simulation:=true

3. run rviz
roslaunch wloam rviz.launch

4. play bag
rosbag play park.bag --clock

If you want to test GPS, just add option enable_gps:=true when start launch file and check the AerialMapDisplay in rviz.
  1. using Livox data
goto https://github.com/KIT-ISAS/lili-om
1. Find and Download bag
using KA_Urban_Schloss_1.bag as example

2. run algorithm
roslaunch wloam run.launch laser_topic:=points_raw imu_topic:=imu/data cloud_format:=velodyne robot_name:=livox odometry_link:=imu_link simulation:=true

3. run convertion for livox data
rosrun wloam livox_converter

4. run rviz
roslaunch wloam rviz.launch

5. play bag
rosbag play KA_Urban_Schloss_1.bag --clock imu/data:=nouse gnss:=gps/fix

If you want to test GPS, just add option enable_gps:=true when start launch file and check the AerialMapDisplay in rviz.

Paper

WLOAM Wheel-LiDAR Odometry and Mapping for Autonomous Vehicles
comming soon...

Imu Odometry is adapted from LIO-SAM

@inproceedings{liosam2020shan,
  title={LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping},
  author={Shan, Tixiao and Englot, Brendan and Meyers, Drew and Wang, Wei and Ratti, Carlo and Rus Daniela},
  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={5135-5142},
  year={2020},
  organization={IEEE}
}

Acknowledgement

This work is inspired by LOAM(Lidar Odometry and Mapping in Real-time) and LIO-SAM(Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping)

Issues
  • Some questions

    Some questions

    Hi,Chen, Thank your for sharing the great work. The test demo is very good.

    Maybe something wrong with the feature extract,the corner features are strange as the figure bellow(the pink is surf and green is corner feature). I use the default parameters.

    The first figure is the bag you provide. 2022-01-21 09-58-09屏幕截图

    And the second figure is my test bag(vlp-16). 2022-01-24 14-24-30屏幕截图

    opened by chengwei0427 0
  • 报错,这是为什么呢

    报错,这是为什么呢

    CMake Error at W-LOAM/src/odometry/CMakeLists.txt:5 (add_executable): Target "imuOdometry_fix_lag" links to target "Boost::timer" but the target was not found. Perhaps a find_package() call is missing for an IMPORTED target, or an ALIAS target is missing?

    opened by HIT-Ygq 0
Owner
Saki-Chen
Saki-Chen
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