用rs_lidar雷达跑lio_sam

2023-05-16

1.准备工作

  • imu绑定串口
  • 有线连接雷达并能用rviz显示雷达点云
  • 用两个imu标定包标定imu
  • 在完成第二步必要的工作后,配置LIO-SAM/config/下的params.yaml参数,更改之前建议备份在旁边复制粘贴一份params(copy).yaml
  • 并更改imu和雷达话题
  • 将rs_lidar数据格式改成velodyne(用了一个ros文件,已加在launch文件中) 

注: 注意 velodyne_points和imu/data前无斜杠(rostopic list里话题是/velodyne_points和/imu/data )

打开前面imu_utils标定的结果按照数字编号对应粘贴覆盖掉params.yaml数值

打开前面lidar_align标定的结果按照数字编号对应粘贴覆盖掉params.yaml数值

params.yaml编号06编号07数值一样都用lidar_align的标定结果编号06三阶矩阵

 

2一些细节上的工作

2.1编译rs_to_velodyne-master功能包(转换激光雷达的数据类型)

2.2lio_sam的LIO-SAM/config/下的params.yaml参数修改

lio_sam:

  # Topics
  pointCloudTopic: "velodyne_points"               # Point cloud data
  imuTopic: "imu/data_open"                         # IMU data
  odomTopic: "odometry/imu"                   # IMU pre-preintegration odometry, same frequency as IMU
  # gpsTopic: "odometry/gps"                   # GPS odometry topic from navsat, see module_navsat.launch file
  gpsTopic: "odometry/gps"
  
  # Frames
  lidarFrame: "base_link"
  baselinkFrame: "base_link"
  odometryFrame: "odom"
  mapFrame: "map"

  # GPS Settings
  useImuHeadingInitialization: false         # if using GPS data, set to "true"
  useGpsElevation: false                      # if GPS elevation is bad, set to "false"
  gpsCovThreshold: 2.0                        # m^2, threshold for using GPS data
  poseCovThreshold: 25.0                      # m^2, threshold for using GPS data
  
  # Export settings
  savePCD: false                              # https://github.com/TixiaoShan/LIO-SAM/issues/3
  savePCDDirectory: "/Downloads/LOAM/"        # in your home folder, starts and ends with "/". Warning: the code deletes "LOAM" folder then recreates it. See "mapOptimization" for implementation

  # Sensor Settings
  sensor: velodyne                            # lidar sensor type, either 'velodyne' or 'ouster'
  N_SCAN: 16                                  # number of lidar channel (i.e., 16, 32, 64, 128)
  Horizon_SCAN: 1800                          # lidar horizontal resolution (Velodyne:1800, Ouster:512,1024,2048)
  downsampleRate: 1                           # default: 1. Downsample your data if too many points. i.e., 16 = 64 / 4, 16 = 16 / 1
  lidarMinRange: 1.0                          # default: 1.0, minimum lidar range to be used
  lidarMaxRange: 1000.0                       # default: 1000.0, maximum lidar range to be used

  # IMU Settings
  imuAccNoise: 1.0151327754116719e-02
  imuGyrNoise: 4.9553027388650394e-03
  imuAccBiasN: 7.4655794718659740e-04
  imuGyrBiasN: 6.3727249626266877e-05
  imuGravity: 9.8035
  imuRPYWeight: 0.01

  # Extrinsics (lidar -> IMU)
  extrinsicTrans: [0.0, 0.0, 0.0]
  extrinsicRot: [1, 0, 0,
                  0, 1, 0,
                  0, 0, 1]
  extrinsicRPY: [1,  0, 0,
                 0, 1, 0,
                  0, 0, 1]
  # extrinsicRot: [1, 0, 0,
  #                 0, 1, 0,
  #                 0, 0, 1]
  # extrinsicRPY: [1, 0, 0,
  #                 0, 1, 0,
  #                 0, 0, 1]

  # LOAM feature threshold
  edgeThreshold: 1.0
  surfThreshold: 0.1
  edgeFeatureMinValidNum: 10
  surfFeatureMinValidNum: 100

  # voxel filter paprams
  odometrySurfLeafSize: 0.4                     # default: 0.4 - outdoor, 0.2 - indoor
  mappingCornerLeafSize: 0.2                    # default: 0.2 - outdoor, 0.1 - indoor
  mappingSurfLeafSize: 0.4                      # default: 0.4 - outdoor, 0.2 - indoor

  # robot motion constraint (in case you are using a 2D robot)
  z_tollerance: 1000                            # meters
  rotation_tollerance: 1000                     # radians

  # CPU Params
  numberOfCores: 4                              # number of cores for mapping optimization
  mappingProcessInterval: 0.15                  # seconds, regulate mapping frequency

  # Surrounding map
  surroundingkeyframeAddingDistThreshold: 1.0   # meters, regulate keyframe adding threshold
  surroundingkeyframeAddingAngleThreshold: 0.2  # radians, regulate keyframe adding threshold
  surroundingKeyframeDensity: 2.0               # meters, downsample surrounding keyframe poses   
  surroundingKeyframeSearchRadius: 50.0         # meters, within n meters scan-to-map optimization (when loop closure disabled)

  # Loop closure
  loopClosureEnableFlag: true
  loopClosureFrequency: 1.0                     # Hz, regulate loop closure constraint add frequency
  surroundingKeyframeSize: 50                   # submap size (when loop closure enabled)
  historyKeyframeSearchRadius: 15.0             # meters, key frame that is within n meters from current pose will be considerd for loop closure
  historyKeyframeSearchTimeDiff: 30.0           # seconds, key frame that is n seconds older will be considered for loop closure
  historyKeyframeSearchNum: 25                  # number of hostory key frames will be fused into a submap for loop closure
  historyKeyframeFitnessScore: 0.3              # icp threshold, the smaller the better alignment

  # Visualization
  globalMapVisualizationSearchRadius: 1000.0    # meters, global map visualization radius
  globalMapVisualizationPoseDensity: 10.0       # meters, global map visualization keyframe density
  globalMapVisualizationLeafSize: 1.0           # meters, global map visualization cloud density

# Navsat (convert GPS coordinates to Cartesian)
navsat:
  frequency: 50
  wait_for_datum: false
  delay: 0.0
  magnetic_declination_radians: 0
  yaw_offset: 0
  zero_altitude: true
  broadcast_utm_transform: false
  broadcast_utm_transform_as_parent_frame: false
  publish_filtered_gps: false

# EKF for Navsat
ekf_gps:
  publish_tf: false
  map_frame: map
  odom_frame: odom
  base_link_frame: base_link
  world_frame: odom

  frequency: 50
  two_d_mode: false
  sensor_timeout: 0.01
  # -------------------------------------
  # External IMU:
  # -------------------------------------
  imu0: imu_correct
  # make sure the input is aligned with ROS REP105. "imu_correct" is manually transformed by myself. EKF can also transform the data using tf between your imu and base_link
  imu0_config: [false, false, false,
                true,  true,  true,
                false, false, false,
                false, false, true,
                true,  true,  true]
  imu0_differential: false
  imu0_queue_size: 50 
  imu0_remove_gravitational_acceleration: true
  # -------------------------------------
  # Odometry (From Navsat):
  # -------------------------------------
  odom0: odometry/gps
  odom0_config: [true,  true,  true,
                 false, false, false,
                 false, false, false,
                 false, false, false,
                 false, false, false]
  odom0_differential: false
  odom0_queue_size: 10

  #                            x     y     z     r     p     y   x_dot  y_dot  z_dot  r_dot p_dot y_dot x_ddot y_ddot z_ddot
  process_noise_covariance: [  1.0,  0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    1.0,  0,    0,    0,    0,    0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    10.0, 0,    0,    0,    0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0.03, 0,    0,    0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0.03, 0,    0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0.1,  0,     0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0.25,  0,     0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0.25,  0,     0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0.04,  0,    0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0.01, 0,    0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0.01, 0,    0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0.5,  0,    0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,    0.01, 0,      0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,    0,    0.01,   0,
                               0,    0,    0,    0,    0,    0,    0,     0,     0,     0,    0,    0,    0,    0,      0.015]

2.3rs_lidar的CMakeLists.txt文件修改了# Custom Point Type (XYZI, XYZIRT)

cmake_minimum_required(VERSION 3.5)
cmake_policy(SET CMP0048 NEW)
project(rslidar_sdk)

#=======================================
# Compile setup (ORIGINAL, CATKIN, COLCON)
#=======================================
set(COMPILE_METHOD CATKIN)

#=======================================
# Custom Point Type (XYZI, XYZIRT)
#=======================================
set(POINT_TYPE XYZIRT)

#========================
# Project details / setup
#========================
set(PROJECT_NAME rslidar_sdk)
add_definitions(-DPROJECT_PATH="${PROJECT_SOURCE_DIR}")
set(CMAKE_BUILD_TYPE RELEASE)
add_definitions(-O3)
add_definitions(-std=c++14)
add_compile_options(-Wall)

#========================
# Dependencies Setup
#========================
#ROS#
find_package(roscpp 1.12 QUIET)
if(roscpp_FOUND)
  message(=============================================================)
  message("-- ROS Found, Ros Support is turned On!")
  message(=============================================================)
  add_definitions(-DROS_FOUND)
  include_directories(${roscpp_INCLUDE_DIRS})
else(roscpp_FOUND)
  message(=============================================================)
  message("-- ROS Not Found, Ros Support is turned Off!")
  message(=============================================================)
endif(roscpp_FOUND)
#ROS2#
find_package(rclcpp QUIET)
if(rclcpp_FOUND AND ${COMPILE_METHOD} STREQUAL "COLCON")
  find_package(ament_cmake REQUIRED)
  find_package(sensor_msgs REQUIRED)
  find_package(rslidar_msg REQUIRED)
  find_package(std_msgs REQUIRED)                      
  set(CMAKE_CXX_STANDARD 14)
  message(=============================================================)
  message("-- ROS2 Found, Ros2 Support is turned On!")
  message(=============================================================)
  add_definitions(-DROS2_FOUND)
  include_directories(${rclcpp_INCLUDE_DIRS})
else(rclcpp_FOUND AND ${COMPILE_METHOD} STREQUAL "COLCON")
  message(=============================================================)
  message("-- ROS2 Not Found, Ros2 Support is turned Off!")
  message(=============================================================)
endif(rclcpp_FOUND AND ${COMPILE_METHOD} STREQUAL "COLCON")
#Protobuf#
find_package(Protobuf QUIET)
find_program(PROTOC protoc)
if(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
  message(=============================================================)
  message("-- Protobuf Found, Protobuf Support is turned On!")
  message(=============================================================)
  add_definitions(-DPROTO_FOUND)
  include_directories(${PROTOBUF_INCLUDE_DIRS})
  SET(PROTO_FILE_PATH ${PROJECT_SOURCE_DIR}/src/msg/proto_msg)
  file(GLOB PROTOBUF_FILELIST ${PROTO_FILE_PATH}/*.proto)
  foreach(proto_file ${PROTOBUF_FILELIST})
    message(STATUS "COMPILING ${proto_file} USING ${PROTOBUF_PROTOC_EXECUTABLE}")
    execute_process(COMMAND ${PROTOBUF_PROTOC_EXECUTABLE}
                    --proto_path=${PROTO_FILE_PATH}
                    --cpp_out=${PROTO_FILE_PATH}
                    ${proto_file})
  endforeach()
else(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
  message(=============================================================)
  message("-- Protobuf Not Found, Protobuf Support is turned Off!")
  message(=============================================================)
endif(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
#Others#
find_package(yaml-cpp REQUIRED)
find_package(PCL QUIET REQUIRED)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
#Catkin#
if(${COMPILE_METHOD} STREQUAL "CATKIN")
  find_package(catkin REQUIRED COMPONENTS
          roscpp
          sensor_msgs
          )

  catkin_package(
          CATKIN_DEPENDS sensor_msgs
  )
endif(${COMPILE_METHOD} STREQUAL "CATKIN")
#Include directory#
include_directories(${PROJECT_SOURCE_DIR}/src)
#Driver core#
add_subdirectory(src/rs_driver)
find_package(rs_driver REQUIRED)
include_directories(${rs_driver_INCLUDE_DIRS})

#========================
# Point Type Definition
#========================
if(${POINT_TYPE} STREQUAL "XYZI")
add_definitions(-DPOINT_TYPE_XYZI)
elseif(${POINT_TYPE} STREQUAL "XYZIRT")
add_definitions(-DPOINT_TYPE_XYZIRT)
endif()
message(=============================================================)
message("-- POINT_TYPE is ${POINT_TYPE}")
message(=============================================================)

#========================
# Build Setup
#========================
#Protobuf#
if(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
  add_executable(rslidar_sdk_node
              node/rslidar_sdk_node.cpp
              src/manager/adapter_manager.cpp
              ${PROTO_FILE_PATH}/packet.pb.cc
              ${PROTO_FILE_PATH}/scan.pb.cc
              ${PROTO_FILE_PATH}/point_cloud.pb.cc
              )
  target_link_libraries(rslidar_sdk_node                   
                      ${PCL_LIBRARIES}
                      ${YAML_CPP_LIBRARIES}
                      ${PROTOBUF_LIBRARY}
                      ${rs_driver_LIBRARIES}
                      )
else(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
  add_executable(rslidar_sdk_node
              node/rslidar_sdk_node.cpp
              src/manager/adapter_manager.cpp
              )
  target_link_libraries(rslidar_sdk_node                   
                      ${PCL_LIBRARIES}
                      ${YAML_CPP_LIBRARIES}
                      ${rs_driver_LIBRARIES}
                      )
endif(NOT PROTOC MATCHES "NOTFOUND" AND Protobuf_FOUND)
#Ros#
if(roscpp_FOUND)
  target_link_libraries(rslidar_sdk_node ${roscpp_LIBRARIES})
endif(roscpp_FOUND)
#Ros2#
if(rclcpp_FOUND AND ${COMPILE_METHOD} STREQUAL "COLCON")
  ament_target_dependencies(rslidar_sdk_node rclcpp sensor_msgs std_msgs rslidar_msg)
  install(TARGETS
    rslidar_sdk_node
    DESTINATION lib/${PROJECT_NAME}
  )
  install(DIRECTORY
    launch
    rviz
    DESTINATION share/${PROJECT_NAME}
  )
  ament_package()
endif(rclcpp_FOUND AND ${COMPILE_METHOD} STREQUAL "COLCON")

2.4将rs_lidar的启动文件start.launch做了修改,加了rs2vc.launch

<launch>
  <node pkg="rslidar_sdk" name="rslidar_sdk_node" type="rslidar_sdk_node" output="screen">
  </node>
  <include file="$(find rs_to_velodyne)/launch/rs2vc.launch" />
 
  <!-- 用cartographer时,将rviz注释掉 , 用AMCL时需将其解开注释-->
  <!-- rviz -->
   <!--<node pkg="rviz" name="rviz" type="rviz" args="-d $(find rslidar_sdk)/rviz/rviz.rviz" /> -->
</launch>

3.到这里准备工作就完成啦,给lidar和imu上电!

3.1启动imu 节点  

roslaunch openzen_sensor openzen_lpms_ig1.launch

3.2 启动rs雷达

roslaunch rslidar_sdk start.launch

3.3启动lio_sam

roslaunch lio_sam run.launch 

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  • 用rs_lidar雷达跑lio_sam

    1 准备工作 imu绑定串口有线连接雷达并能用rviz显示雷达点云用两个imu标定包标定imu在完成第二步必要的工作后 xff0c 配置LIO SAM config 下的params yaml参数 xff0c 更改之前建议备份在旁边复制粘贴