基于mid-360的FAST_LIO2,Point-LIO,faster-lio,LIO-SAM部署(持续更新)_faster-lio mid360

硬件：orangepi5 8G+32G (RK3588S ARM64)

系统：ubuntu 20.04

FAST_LIO2：

1.编译livox-SDK2

git clone https://github.com/Livox-SDK/Livox-SDK2.git
cd ./Livox-SDK2/
mkdir build && cd build
cmake .. && make -j8
sudo make install

2.编译FAST_LIO

2.1 创建工作空间

mkdir FAST-LIO2 && cd FAST-LIO2
mkdir src && cd src

2.2 下载livox_ros_driver2源码

git clone https://github.com/Livox-SDK/livox_ros_driver2.git
cd livox_ros_driver2
./build.sh ROS1

2.3 下载FAST_LIO2源码

git clone https://github.com/hku-mars/FAST_LIO.git
cd FAST_LIO
git submodule update --init
cd ../..

3.修改FAST_LIO代码

3.1 FAST_LIO2的CMakelists.txt

find_package(catkin REQUIRED COMPONENTS
  ...
  livox_ros_driver
  ...
)

改为

find_package(catkin REQUIRED COMPONENTS
  ...
  livox_ros_driver2
  ...
)

3.2 FAST_LIO2的package.xml

<build_depend>livox_ros_driver</build_depend>
<run_depend>livox_ros_driver</run_depend>

改为

<build_depend>livox_ros_driver2</build_depend>
<run_depend>livox_ros_driver2</run_depend>

3.3 FAST_LIO2的头文件引用

用vscode的搜索一键替换

#include <livox_ros_driver/CustomMsg.h>

改为

#include <livox_ros_driver2/CustomMsg.h>

3.4 FAST_LIO2的命名空间

用vscode的搜索一键替换

livox_ros_driver::

改为

livox_ros_driver2::

编译：

catkin_make

Point-LIO:

1.编译livox-SDK

git clone https://github.com/Livox-SDK/Livox-SDK.git
cd Livox-SDK
cd build && cmake ..
make -j8
sudo make install

2.编译Point-LIO

2.1 编译livox_ros_driver

mkdir -p Point-LIO/src #-p  代表递归创建文件夹
cd Point-LIO/src
git clone https://github.com/Livox-SDK/livox_ros_driver.git
cd ..
catkin_make

2.1 编译Point-LIO

cd src
git clone https://github.com/hku-mars/Point-LIO.git
cd ..
catkin_make

  src/config 文件夹下增加的 mid360.yaml 文件配置:

common:
    lid_topic:  "/livox/lidar" 
    imu_topic:  "/livox/imu" 
    con_frame: false # true: if you need to combine several LiDAR frames into one
    con_frame_num: 1 # the number of frames combined
    cut_frame: false # true: if you need to cut one LiDAR frame into several subframes
    cut_frame_time_interval: 0.1 # should be integral fraction of 1 / LiDAR frequency
    time_lag_imu_to_lidar: 0.0 # Time offset between LiDAR and IMU calibrated by other algorithms, e.g., LI-Init (find in Readme)
                               # the timesample of IMU is transferred from the current timeline to LiDAR's timeline by subtracting this value
 
preprocess:
    lidar_type: 1 
    scan_line: 4
    timestamp_unit: 1           # the unit of time/t field in the PointCloud2 rostopic: 0-second, 1-milisecond, 2-microsecond, 3-nanosecond.
    blind: 0.5 
 
mapping:
    imu_en: true
    start_in_aggressive_motion: false # if true, a preknown gravity should be provided in following gravity_init
    extrinsic_est_en: false # for aggressive motion, set this variable false
    imu_time_inte: 0.005 # = 1 / frequency of IMU
    satu_acc: 3.0 # the saturation value of IMU's acceleration. not related to the units
    satu_gyro: 35 # the saturation value of IMU's angular velocity. not related to the units
    acc_norm: 1.0 # 1.0 for g as unit, 9.81 for m/s^2 as unit of the IMU's acceleration
    lidar_meas_cov: 0.001 # 0.001; 0.01
    acc_cov_output: 500
    gyr_cov_output: 1000 
    b_acc_cov: 0.0001 
    b_gyr_cov: 0.0001 
    imu_meas_acc_cov: 0.1 #0.1 # 0.1
    imu_meas_omg_cov: 0.1 #0.01 # 0.1
    gyr_cov_input: 0.01 # for IMU as input model
    acc_cov_input: 0.1 # for IMU as input model
    plane_thr: 0.1 # 0.05, the threshold for plane criteria, the smaller, the flatter a plane
    match_s: 81
    fov_degree: 360 
    det_range: 100
    gravity_align: true # true to align the z axis of world frame with the direction of gravity, and the gravity direction should be specified below
    gravity: [0.0, 0.0, -9.810] # [0.0, 9.810, 0.0] # gravity to be aligned
    gravity_init: [0.0, 0.0, -9.810] # [0.0, 9.810, 0.0] # # preknown gravity in the first IMU body frame, use when imu_en is false or start from a non-stationary state
    extrinsic_T: [ -0.011, -0.02329, 0.04412 ]
    extrinsic_R: [ 1, 0, 0,
                   0, 1, 0,
                   0, 0, 1 ]
 
odometry: 
    publish_odometry_without_downsample: false
 
publish:
    path_en: true                 # false: close the path output
    scan_publish_en: true         # false: close all the point cloud output
    scan_bodyframe_pub_en: false  # true: output the point cloud scans in IMU-body-frame
 
pcd_save:
    pcd_save_en: false
    interval: -1                 # how many LiDAR frames saved in each pcd file; 
                                 # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.

 src/launch 文件夹下增加 mapping_mid360.launch 文件： 

<launch>
<!-- Launch file for Livox AVIA LiDAR -->
 
	<arg name="rviz" default="true" />
 
	<node pkg="point_lio" type="pointlio_mapping" name="laserMapping" output="screen">
	<rosparam command="load" file="$(find point_lio)/config/mid360.yaml" />
	<param name="use_imu_as_input" type="bool" value="1"/> <!--change to 1 to use IMU as input of Point-LIO-->
	<param name="prop_at_freq_of_imu" type="bool" value="1"/>
	<param name="check_satu" type="bool" value="1"/>
	<param name="init_map_size" type="int" value="10"/>
	<param name="point_filter_num" type="int" value="1"/> <!--4, 3--> 
	<param name="space_down_sample" type="bool" value="1" />  
	<param name="filter_size_surf" type="double" value="0.3" /> <!--0.5, 0.3, 0.2, 0.15, 0.1--> 
	<param name="filter_size_map" type="double" value="0.2" /> <!--0.5, 0.3, 0.15, 0.1-->
	<param name="cube_side_length" type="double" value="2000" /> <!--1000-->
	<param name="runtime_pos_log_enable" type="bool" value="0" /> <!--1-->
	</node>
	<group if="$(arg rviz)">
	<node launch-prefix="nice" pkg="rviz" type="rviz" name="rviz" args="-d $(find point_lio)/rviz_cfg/loam_livox.rviz" />
	</group>
 
	launch-prefix="gdb -ex run --args"
 
</launch>

运行

roslaunch point_lio mapping_mid360.launch

faster-lio

1.编译livox-SDK

git clone https://github.com/Livox-SDK/Livox-SDK.git
cd Livox-SDK
cd build && cmake ..
make -j8
sudo make install

2.编译faster-lio 

2.1 编译livox_ros_driver

mkdir -p Point-LIO/src #-p  代表递归创建文件夹
cd Point-LIO/src
git clone https://github.com/Livox-SDK/livox_ros_driver.git
cd ..
catkin_make

2.2  编译faster-lio

mkdir -p faster_lio_ws/src
cd faster_lio_ws/src
git clone https://github.com/gaoxiang12/faster-lio.git
cd ..
catkin_make

src/config 文件夹下增加的 mid360.yaml 文件配置

common:
  lid_topic: "/livox/lidar"
  imu_topic: "/livox/imu"
  time_sync_en: false         # ONLY turn on when external time synchronization is really not possible
 
preprocess:
  lidar_type: 1                # 1 for Livox serials LiDAR, 2 for Velodyne LiDAR, 3 for ouster LiDAR,
  scan_line: 4
  blind: 0.5
  time_scale: 1e-3
 
mapping:
  acc_cov: 0.1
  gyr_cov: 0.1
  b_acc_cov: 0.0001
  b_gyr_cov: 0.0001
  fov_degree: 360
  det_range: 100.0
  extrinsic_est_en: false      # true: enable the online estimation of IMU-LiDAR extrinsic
  extrinsic_T: [ -0.011, -0.02329, 0.04412  ]
  extrinsic_R: [ 1, 0, 0,
                 0, 1, 0,
                 0, 0, 1 ]
 
publish:
  path_publish_en: false
  scan_publish_en: true       # false: close all the point cloud output
  scan_effect_pub_en: true    # true: publish the pointscloud of effect point
  dense_publish_en: false       # false: low down the points number in a global-frame point clouds scan.
  scan_bodyframe_pub_en: true  # true: output the point cloud scans in IMU-body-frame
 
path_save_en: true                 # 保存轨迹，用于精度计算和比较
 
pcd_save:
  pcd_save_en: true
  interval: -1                 # how many LiDAR frames saved in each pcd file;
  # -1 : all frames will be saved in ONE pcd file, may lead to memory crash when having too much frames.
 
feature_extract_enable: false
point_filter_num: 3
max_iteration: 3
filter_size_surf: 0.5
filter_size_map: 0.5             # 暂时未用到，代码中为0， 即倾向于将降采样后的scan中的所有点加入map
cube_side_length: 1000
 
ivox_grid_resolution: 0.5        # default=0.2
ivox_nearby_type: 18             # 6, 18, 26
esti_plane_threshold: 0.1        # default=0.1

在 src/launch 文件夹下增加 mapping_mid360.launch：

<launch>
<!-- Launch file for Livox AVIA LiDAR -->
 
	<arg name="rviz" default="true" />
 
	<rosparam command="load" file="$(find faster_lio)/config/mid360.yaml" />
 
	<param name="feature_extract_enable" type="bool" value="0"/>
	<param name="point_filter_num_" type="int" value="3"/>
	<param name="max_iteration" type="int" value="3" />
	<param name="filter_size_surf" type="double" value="0.5" />
	<param name="filter_size_map" type="double" value="0.5" />
	<param name="cube_side_length" type="double" value="1000" />
	<param name="runtime_pos_log_enable" type="bool" value="1" />
    <node pkg="faster_lio" type="run_mapping_online" name="laserMapping" output="screen" />
 
	<group if="$(arg rviz)">
	<node launch-prefix="nice" pkg="rviz" type="rviz" name="rviz" args="-d $(find faster_lio)/rviz_cfg/loam_livox.rviz" />
	</group>
 
</launch>

运行：

roslaunch faster_lio mapping_mid360.launch

LIO-SAM：

 1.编译livox-SDK

git clone https://github.com/Livox-SDK/Livox-SDK.git
cd Livox-SDK
cd build && cmake ..
make -j8
sudo make install

2.编译LIO-SAM

2.1 编译livox_ros_driver

mkdir -p Point-LIO/src #-p  代表递归创建文件夹
cd Point-LIO/src
git clone https://github.com/Livox-SDK/livox_ros_driver.git
cd ..
catkin_make

2.2  编译faster-lio

依赖：

sudo apt-get install -y ros-noetic-navigation
sudo apt-get install -y ros-noetic-robot-localization
sudo apt-get install -y ros-noetic-robot-state-publisher
sudo add-apt-repository ppa:borglab/gtsam-release-4.0
sudo apt install libgtsam-dev libgtsam-unstable-dev

下载代码：

mkdir -p LIOSAM/src
cd LIOSAM/src
git clone https://github.com/nkymzsy/LIO-SAM-MID360.git

修改CMakelists：

C++11  改成C++14

修改src/LIO-SAM-MID360-master/include 目录下，utility.h 文件

#include <opencv/cv.h> 改为 #include <opencv2/opencv.hpp>
 
#include <pcl/kdtree/kdtree_flann.h> 头文件放到 #include <opencv2/opencv.hpp>前面

编译：

cd ~/LIOSAM
catkin_make

启动

roslaunch lio_sam run6axis.launch

LIOSAM-mid360的yaml文件的参数好像有点问题，会飘，通常出现在雷达和IMU没标定好的情况。过两天测试好再更新这些问题解决办法。

感觉大佬的部署教学，有些部署错误这里已修改多层长走廊场景下Fast-Lio2、Point-Lio、LIO-SAM、Faster-Lio建图对比视频_哔哩哔哩_bilibili