cartographer保存地图,如何做笔记

cartographer-ros使用指南1，cartographer-ros安装： 1.1安装cartographer 1.2安装cartographer-ROS2，使用官方数据集安装cartographer-ROS2

一、Cartographer-ros安装： 1.1cartographer安装

参考官方文档安装即可。

3359谷歌- cartographer.readthedocs.io/en/latest /

1.2cartographer-ROS的安装也参考官方文档进行安装即可。

3359谷歌- cartographer-ROS.readthedocs.io/en/latest/your _ bag.html

本人的实现与官方略有不同，但遵循以下步骤。

创建并初始化新的ros工作区： mkdir carto _ wscdcarto _ wsmkdirsrccdsrccatkin _ init _ workspacecartograher _ ROS下载： git clolos 伊尔： catkin_make二、使用官方数据集跑cartographer的详细情况请参照官方手册：

3359谷歌- cartographer-ROS.readthedocs.io/en/latest/demos.html

三、使用VLP-16跑cartographer 3.1二维定位和施工图：一、准备文件：

在cartographer _ ROS/configuration _ files中，创建my_mapping_2d.lua

在cartographer_ros/launch上，单击my _ mapping _ 2d.launch http://www.Sina.com /

将my_mapping_2d.lua修改如下：

二、设定参数：

include ' map _ builder.Lua ' include ' trajectory _ builder.Lua ' options={ map _ builder=map _ builder，tra jectector published_frame='base_link '，Odom _ frame=' Odom publish _ frame _ projected _ to _ 2d=false，u u odomed use _ landmarks=false num _ multi _ echo _ laser _ scans=0，num _ subdivisions _ per _ laser _ scan=1，num _ pose_publish_period_sec=5e-3，trajectory _ publish _ period _ sec odometry _ sampling _ ratio=1.固定lanng } map _ builder.use _ trajectory _ builder _ 2d=true trajectory _ builder _ 2d.sub maps.num _ range _ data=35 TTA length=1. trajectory _ builder _ 2d lative _ scan _ matching=true trajectory _ builder _ 2d.real _ time _ corerelarer

r_search_window = 0.1TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.translation_delta_cost_weight = 10.TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.rotation_delta_cost_weight = 1e-1 POSE_GRAPH.optimization_problem.huber_scale = 1e2POSE_GRAPH.optimize_every_n_nodes = 35POSE_GRAPH.constraint_builder.min_score = 0.65 return options

三、修改launch文件：
   my_mapping_2d.launch如下所示：

<launch> <node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" /> <node name="cartographer_node" pkg="cartographer_ros" type="cartographer_node" args=" -configuration_directory $(find cartographer_ros)/configuration_files -configuration_basename my_mapping_2d.lua" output="screen"> <!-- 修改scan为自己雷达发布的话题 --> <remap from="echoes" to="scan" /> <!-- 修改imu为自己imu发布的话题，如果没有或者不使用imu，则注释掉下行 --> <remap from="imu" to="imu/data_own" /> </node> <node name="cartographer_occupancy_grid_node" pkg="cartographer_ros" type="cartographer_occupancy_grid_node" args="-resolution 0.05" /> <node name="rviz" pkg="rviz" type="rviz" required="true" args="-d $(find cartographer_ros)/configuration_files/demo_2d.rviz" /></launch>

四、运行程序：

roslaunch cartographer_ros my_mapping_2d.launch 3.2 三维定位与建图：

一、准备文件：
   在cartographer_ros/configuration_files中，创建my_mapping_3d.lua
   在cartographer_ros/launch中，创建my_mapping_3d.launch
   在cartographer_ros/urdf中，创建my_car.urdf.xacro
二、设定参数：
   修改my_mapping_3d.lua，如下所示。
   具体参数设置见官方文档：Lua configuration reference documentation

include "map_builder.lua"include "trajectory_builder.lua"options = { map_builder = MAP_BUILDER, trajectory_builder = TRAJECTORY_BUILDER, map_frame = "map", tracking_frame = "imu_link", published_frame = "base_link", odom_frame = "odom", provide_odom_frame = true, publish_frame_projected_to_2d = false, use_pose_extrapolator = true, use_odometry = false, use_nav_sat = false, use_landmarks = false, num_laser_scans = 0, num_multi_echo_laser_scans = 0, num_subdivisions_per_laser_scan = 1, num_point_clouds = 1, -- 这里设置成自己的雷达的数量，一般为1 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.,}TRAJECTORY_BUILDER_3D.num_accumulated_range_data = 1 -- 积累多少帧发布一次数据， 设置为1MAP_BUILDER.use_trajectory_builder_3d = trueMAP_BUILDER.num_background_threads = 7POSE_GRAPH.optimization_problem.huber_scale = 5e2POSE_GRAPH.optimize_every_n_nodes = 100-- 每次优化间隔的node数POSE_GRAPH.constraint_builder.sampling_ratio = 0.03POSE_GRAPH.optimization_problem.ceres_solver_options.max_num_iterations = 10POSE_GRAPH.constraint_builder.min_score = 0.62POSE_GRAPH.constraint_builder.global_localization_min_score = 0.66return options

三、修改launch文件：
   my_mapping_3d.launch如下所示：

<launch> <param name="robot_description" textfile="$(find cartographer_ros)/urdf/my_car.urdf.xacro" /> <node name="robot_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher" /> <node name="cartographer_node" pkg="cartographer_ros" type="cartographer_node" args=" -configuration_directory $(find cartographer_ros)/configuration_files -configuration_basename my_mapping_3d.lua" output="screen"> <remap from="points2" to="/velodyne_points" /> <remap from="/imu" to="/imu/data_own" /> </node> <node name="cartographer_occupancy_grid_node" pkg="cartographer_ros" type="cartographer_occupancy_grid_node" args="-resolution 0.05" /> <node name="rviz" pkg="rviz" type="rviz" required="true" args="-d $(find cartographer_ros)/configuration_files/demo_3d.rviz" /></launch>

三、创建自己的机器人模型：

<?xml version="1.0" ?><robot name="vdcar" xmlns:xacro="http://ros.org/wiki/xacro"> <xacro:include filename="$(find vdcar)/urdf/common_properties.xacro"/> <!--xacro:include filename="$(find turtlebot3_description)/urdf/turtlebot3_waffle2d.gazebo.xacro"/--> <link name="base_footprint"/> <joint name="base_joint" type="fixed"> <parent link="base_footprint"/> <child link="base_link" /> <origin xyz="0 0 0.12065" rpy="0 0 0"/> </joint> <link name="base_link" /> <!--sure--> <joint name="imu_joint" type="fixed"> <parent link="base_link"/> <child link="imu_link"/> <origin xyz="0.0583 -0.0434 0.2123" rpy="0 0 0"/> <axis xyz="0 0 1" /> </joint> <link name="imu_link"/> <!--sure--> <joint name="velodyne_joint" type="fixed"> <parent link="base_link"/> <child link="velodyne"/> <origin xyz="0.355 0 0.9188017" rpy="0 0 0"/> <axis xyz="0 0 1" /> </joint> <link name="velodyne"/> </robot>

五、运行程序：

roslaunch cartographer_ros my_mapping_3d.launch