LIO-EKF: 运行数据UrbanNav与mid360设备详细教程

news2024/11/24 5:04:30

一、代码连接

代码下载连接：

YibinWu/LIO-EKF: Maybe the simplest LiDAR-inertial odometry that one can have. (github.com)

编译步骤：

cd src
git clone git@github.com:YibinWu/LIO-EKF.git
catkin_make
source devel/setup.bash

运行步骤：

Replace the path to the rosbag (bagfile) in the launch files with your own path.

roslaunch lio_ekf urbanNav20210517.launch
roslaunch lio_ekf street_01.launch
roslaunch lio_ekf short_exp.launch

运行结果如下：

三、问题及其解决方案

问题1：成功编译，运行roslaunch lio_ekf urbanNav20210517.launch ，rviz没有轨迹出来，检查topic都没有问题。

解决：把topic在代码中修改即可，修改代码地方如下图：

或

config文件中的 lid_topic 修改成 lidar_topic

四、跑通mid360设备采集的数据

4.1 启动mid360的SDK驱动

具体连接：全网最详细的 Ubuntu 18.04 安装Livox mid-360驱动,测试 fast_lio2_ubuntu mid360 fastlio-CSDN博客

cd Livox-SDK2_ROS_driver
source devel/setup.bash
roslaunch livox_ros_driver2 rviz_MID360.launch //一定运行这个launch

4.2 修改LIO-EKF代码

把IMU数据中的加速度乘以9.8，因为mid360采集IMU数据时，加速度的单位是g，角速度的单位是rad/s.

4.3 增加并修改mid360.yaml的配置文件

内容如下：

common:
    lidar_topic:  "/livox/lidar" 
    imu_topic:  "/livox/imu" 

lidar:
    deskew: true
    preprocess: true
    max_range: 100.0 
    min_range: 5.0
    max_points_per_voxel: 20
    voxel_size: 1
    max_iteration: 1

# imu:
#     # IMU noise parameters
#     arw: [1087, 1087, 1087]                       # [deg/sqrt(hr)]    1087, 1087, 1087
#     vrw: [18.9, 18.9, 18.9]                           # [m/s/sqrt(hr)]    18.9, 18.9, 18.9
#     gbstd: [2063.0, 2063.0, 2063.0]        # [deg/hr]                2063.0, 2063.0, 2063.0
#     abstd: [1000.0, 1000.0, 1000.0]        # [mGal]                   1000.0, 1000.0, 1000.0
#     corrtime: 1.0                    # [hr]
imu:
    # IMU noise parameters
    arw: [2, 2, 2]           # [deg/sqrt(hr)]
    vrw: [4, 4, 4]          # [m/s/sqrt(hr)]
    gbstd: [20.0, 20.0, 20.0]        # [deg/hr]
    abstd: [500.0, 500.0, 500.0]     # [mGal]
    corrtime: 1.0                    # [hr]


lio:
    # initial position std, north, east and down in n-frame. [m, m, m]
    initposstd: [ 0.05, 0.05, 0.05 ]
    # initial velocity std, north, east and down speed in n-frame. [m/s, m/s, m/s]
    initvelstd: [ 0.05, 0.05, 0.05 ]
    # initial attitude std, roll, pitch and yaw std. [deg, deg, deg]
    initattstd: [ 0.1, 0.1, 0.1 ]
 
    extrinsic_T: [-0.011, -0.02329, 0.04412]
    extrinsic_R: [ 1, 0, 0, 
                    0, 1, 0, 
                    0, 0, 1]
    #transform the imu frame to front-right-down (which is used in the code)
    #换成自己的设备，这个参数需要改一下。mid360: 前左上，对应的imu_tran_R如下：
    imu_tran_R: [1,0,0,
                     0,-1,0,
                    0,0,-1]

4.4 增加并修改Mid_360.launch的配置文件

内容如下：

<?xml version="1.0"?>
<launch>

  <rosparam command="load" file="$(find lio_ekf)/config/mid360_lioekf.yaml" />

  <!-- ROS paramaters -->
  <arg name="visualize" default="true"/>
  <arg name="odom_frame" default="odom"/>
 

  <param name="outputdir" type="string" value="$(find lio_ekf)/output/" />

  <!-- Odometry node -->
  <node pkg="lio_ekf" type="lio_ekf_node" name="lio_ekf_node" output="screen"/>

  
  <!-- Visualizer -->
  <group if="$(arg visualize)">
    <node pkg="rviz" type="rviz" name="rviz" args="-d $(find lio_ekf)/rviz/lio_ekf.rviz"/>
  </group>
  
</launch>