Cartographer学习

官方文档：Compiling Cartographer ROS — Cartographer ROS documentation

 动手学ROS2

1、源码安装

git clone https://ghproxy.com/https://github.com/ros2/cartographer.git -b ros2
git clone https://ghproxy.com/https://github.com/ros2/cartographer_ros.git -b ros2

2、安装依赖

wget http://fishros.com/install -O fishros && . fishros

选择编号3，然后运行
rodepc update

 3、编译

colcon build --packages-up-to cartographer_ros 

4、查看安装是否成功

ros2 pkg list | grep cartographer

成功显示：

cartographer_ros
cartographer_ros_msgs

 ------------------------------------------------------------------------------------------------------------------------------

二进制安装

sudo apt install ros-humble-cartographer -y

sudo apt install ros-humble-cartographer-ros -y

 5、配置参数

创建一个.lua文件,根据情况配置

include "map_builder.lua"
include "trajectory_builder.lua"

options = {
  map_builder = MAP_BUILDER,
  trajectory_builder = TRAJECTORY_BUILDER,
  map_frame = "map",
  tracking_frame = "base_link",
  -- base_link改为odom,发布map到odom之间的位姿态
  published_frame = "odom",
  odom_frame = "odom",
  -- true改为false，不用提供里程计数据
  provide_odom_frame = false,
  -- false改为true，仅发布2D位资
  publish_frame_projected_to_2d = true,
  -- false改为true，使用里程计数据
  use_odometry = true,
  use_nav_sat = false,
  use_landmarks = false,
  -- 0改为1,使用一个雷达
  num_laser_scans = 1,
  -- 1改为0，不使用多波雷达
  num_multi_echo_laser_scans = 0,
  -- 10改为1，1/1=1等于不分割
  num_subdivisions_per_laser_scan = 1,
  num_point_clouds = 0,
  lookup_transform_timeout_sec = 0.2,
  submap_publish_period_sec = 0.3,
  pose_publish_period_sec = 5e-3,
  trajectory_publish_period_sec = 30e-3,
  rangefinder_sampling_ratio = 1.,
  odometry_sampling_ratio = 1.,
  fixed_frame_pose_sampling_ratio = 1.,
  imu_sampling_ratio = 1.,
  landmarks_sampling_ratio = 1.,
}


-- false改为true，启动2D SLAM
MAP_BUILDER.use_trajectory_builder_2d = true

-- 0改成0.10,比机器人半径小的都忽略
TRAJECTORY_BUILDER_2D.min_range = 0.10
-- 30改成3.5,限制在雷达最大扫描范围内，越小一般越精确些
TRAJECTORY_BUILDER_2D.max_range = 3.5
-- 5改成3,传感器数据超出有效范围最大值
TRAJECTORY_BUILDER_2D.missing_data_ray_length = 3.
-- true改成false,不使用IMU数据，大家可以开启，然后对比下效果
TRAJECTORY_BUILDER_2D.use_imu_data = false
-- false改成true,使用实时回环检测来进行前端的扫描匹配
TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true 
-- 1.0改成0.1,提高对运动的敏感度
TRAJECTORY_BUILDER_2D.motion_filter.max_angle_radians = math.rad(0.1)

-- 0.55改成0.65,Fast csm的最低分数，高于此分数才进行优化。
POSE_GRAPH.constraint_builder.min_score = 0.65
--0.6改成0.7,全局定位最小分数，低于此分数则认为目前全局定位不准确
POSE_GRAPH.constraint_builder.global_localization_min_score = 0.7

-- 设置0可关闭全局SLAM
-- POSE_GRAPH.optimize_every_n_nodes = 0

return options

 6、编写launch文件

import os
from launch import LaunchDescription
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import Node
from launch_ros.substitutions import FindPackageShare


def generate_launch_description():
    # 定位到功能包的地址
    pkg_share = FindPackageShare(package='fishbot_cartographer').find('fishbot_cartographer')
    
    #=====================运行节点需要的配置=======================================================================
    # 是否使用仿真时间，我们用gazebo，这里设置成true
    use_sim_time = LaunchConfiguration('use_sim_time', default='true')
    # 地图的分辨率
    resolution = LaunchConfiguration('resolution', default='0.05')
    # 地图的发布周期
    publish_period_sec = LaunchConfiguration('publish_period_sec', default='1.0')
    # 配置文件夹路径
    configuration_directory = LaunchConfiguration('configuration_directory',default= os.path.join(pkg_share, 'config') )
    # 配置文件
    configuration_basename = LaunchConfiguration('configuration_basename', default='fishbot_2d.lua')
    rviz_config_dir = os.path.join(pkg_share, 'config')+"/cartographer.rviz"
    print(f"rviz config in {rviz_config_dir}")

    
    #=====================声明三个节点，cartographer/occupancy_grid_node/rviz_node=================================
    cartographer_node = Node(
        package='cartographer_ros',
        executable='cartographer_node',
        name='cartographer_node',
        output='screen',
        parameters=[{'use_sim_time': use_sim_time}],
        arguments=['-configuration_directory', configuration_directory,
                   '-configuration_basename', configuration_basename])

    cartographer_occupancy_grid_node = Node(
        package='cartographer_ros',
        executable='cartographer_occupancy_grid_node',
        name='cartographer_occupancy_grid_node',
        output='screen',
        parameters=[{'use_sim_time': use_sim_time}],
        arguments=['-resolution', resolution, '-publish_period_sec', publish_period_sec])

    rviz_node = Node(
        package='rviz2',
        executable='rviz2',
        name='rviz2',
        arguments=['-d', rviz_config_dir],
        parameters=[{'use_sim_time': use_sim_time}],
        output='screen')

    #===============================================定义启动文件========================================================
    ld = LaunchDescription()
    ld.add_action(cartographer_node)
    ld.add_action(cartographer_occupancy_grid_node)
    ld.add_action(rviz_node)

    return ld

7、保存地图

安装保存地图软件

sudo apt install ros-humble-nav2-map-server

保存地图命令

ros2 run nav2_map_server map_saver_cli -t /map -f mapname # -t 订阅的话题名，-f 保存地图名