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世界热点!google官方安装指导:installation跑数据集

来源:CSDN 时间:2023-04-03 11:23:59

问题: 1、官方下载地址; 2、官方文档;


(资料图片仅供参考)

安装

参考博文https://blog.csdn.net/weixin_39784658/article/details/99452960 官方安装指导https://google-cartographer-ros.readthedocs.io/en/latest/compilation.html#building-installation

跑数据集

此部分参考博文 http://www.freesion.com/article/9794248452/

下载数据集

wget -P ~/Downloads https://storage.googleapis.com/cartographer-public-data/bags/backpack_2d/b2-2016-04-05-14-44-52.bagwget -P ~/Downloads https://storage.googleapis.com/cartographer-public-data/bags/backpack_2d/b2-2016-04-27-12-31-41.bag

跑数据集建图

roslaunch cartographer_ros offline_backpack_2d.launch bag_filenames:=${HOME}/Downloads/b2-2016-04-05-14-44-52.bag

跑数据集纯定位测试

roslaunch cartographer_ros demo_backpack_2d_localization.launch \   load_state_filename:=${HOME}/Downloads/b2-2016-04-05-14-44-52.bag.pbstream \   bag_filename:=${HOME}/Downloads/b2-2016-04-27-12-31-41.bag

这里后面两个参数一个是上一步建好的地图,pbstream格式,另一个是数据集。也就是说,先用第一个数据集建图,建完图后用第二个数据集进行定位测试。

主要修改文件及参数

依据原有参考文件新建文件

文件对应关系

backpack_2d.launch -> my_robot_2d.launch demo_backpack_2d.launch -> demo_my_robot_2d.launch offline_backpack_2d.launch -> offline_my_robot_2d.launch demo_backpack_2d_localization.launch -> demo_my_robot_localization_2d.launch assets_writer_backpack_2d.launch -> assets_writer_my_robot_2d.launch

backpack_2d.lua -> my_robot_2d.lua backpack_2d_localization.lua -> my_robot_2d_localization.lua aasets_writer_backpack_2d.lua -> aasets_writer_my_robot_2d.lua

建图

参考博文https://blog.csdn.net/m0_37672916/article/details/77198261

建图操作流程

主要包含:激光雷达、移动机器人(轮椅)、cartographer。

1、启动激光雷达

roslaunch urg_node urg_lidar.launch

2、启动轮椅

rosrun wheel_chair wheel_driver

3、启动建图

roslaunch cartographer_ros demo_revo_lds.launch

备注:不需要里程信息,也可以建图;在建图过程中,轮椅编码器未转动。

可将如上流程写成launch文件:

主要注意:TF、Topic

TF-tree关系

map |----odom        |----base_footprint(差动轮中心)                 |---- base_link(轮椅)                            |----base_scan(激光雷达)

坐标间关系建立

1、轮椅建立odom、base_footprint、base_link、base_scan三者之间的关系。 其中, base_footprint、base_link、base_scan,三者之间为固定关系,可在launch文件中建立为静态坐标系,固定周期发布; base_footprint相对于odom为里程关系,根据运动实时计算里程计推算的位姿,需要实时发布; 2、Cartographer查阅TF-tree上的base_scan相对于map的关系,根据激光点云定位base_scan,并根据base_link与base_scan的关系追踪base_link的位姿,最终推算odom相对于map的位姿关系并发布。简而言之,cartographer通过修整odom相对于map的关系,从而定位机器人base_link相对于map的关系。 在.lua配置文件中设定如下值:

map_frame = "map",tracking_frame = "base_link",published_frame = "odom",odom_frame = "odom",provide_odom_frame = false,use_odometry = true,

保存地图

不再接受进一步数据

rosservice call /finish_trajectory 0

序列化保存其当前状态

rosservice call /write_state "{filename: "${HOME}/Downloads/mymap_name.pbstream"}"

将pbstream转换为pgm和yaml

rosrun cartographer_ros cartographer_pbstream_to_ros_map  -map_filestem=${HOME}/Downloads/mymap_name  -pbstream_filename=${HOME}/Downloads/mymap_name.pbstream -resolution=0.05

纯定位

启动文件:

导航

启动文件:

附件

主要更改的文件

my_robot_2d_localization.lua 文件功能:配置机器人纯定位的相关参数。保证定位过程中的低延时特性。

include "my_robot_2d.lua"-- TRAJECTORY_BUILDER.pure_localization_trimmer = {--     max_submaps_to_keep = 3, -- 最大保存子图数,存定位模式通过子图进行定位,但只需要当前和上一个子图即可,我这里设置的是2--   }TRAJECTORY_BUILDER.pure_localization = truePOSE_GRAPH.optimize_every_n_nodes = 20-- output map to base_link for evaluation-- options.provide_odom_frame = false-- POSE_GRAPH.optimization_problem.log_solver_summary = true-- fast localizationMAP_BUILDER.num_background_threads = 8POSE_GRAPH.constraint_builder.sampling_ratio = 0.5 * POSE_GRAPH.constraint_builder.sampling_ratioPOSE_GRAPH.global_sampling_ratio = 0.1 * POSE_GRAPH.global_sampling_ratioPOSE_GRAPH.max_num_final_iterations = 1return options

my_robot_2d.lua 文件功能:配置机器人相关参数,主要坐标系名称、是否有里程计/卫星/地标,传感器数量,传感器测量范围等。

include "map_builder.lua"include "trajectory_builder.lua"options = {  map_builder = MAP_BUILDER,  trajectory_builder = TRAJECTORY_BUILDER,  map_frame = "map",  tracking_frame = "base_link",  published_frame = "base_link",  odom_frame = "odom",  provide_odom_frame = true,  publish_frame_projected_to_2d = true,  use_odometry = true,  use_nav_sat = false,  use_landmarks = false,  num_laser_scans = 1,  num_multi_echo_laser_scans = 0,  num_subdivisions_per_laser_scan = 10,  num_point_clouds = 0,  lookup_transform_timeout_sec = 0.2,  submap_publish_period_sec = 0.3,  pose_publish_period_sec = 10e-3,  trajectory_publish_period_sec = 30e-3,  rangefinder_sampling_ratio = 1.,  odometry_sampling_ratio = 1.,  fixed_frame_pose_sampling_ratio = 1.,  imu_sampling_ratio = 1e-3,  landmarks_sampling_ratio = 1.,}MAP_BUILDER.use_trajectory_builder_2d = trueTRAJECTORY_BUILDER_2D.num_accumulated_range_data = 10TRAJECTORY_BUILDER_2D.use_imu_data = falseTRAJECTORY_BUILDER_2D.min_range = 0.1,TRAJECTORY_BUILDER_2D.max_range = 8.0,TRAJECTORY_BUILDER_2D.min_z = -0.05,TRAJECTORY_BUILDER_2D.max_z = 0.5,TRAJECTORY_BUILDER_2D.missing_data_ray_length = 8.0POSE_GRAPH.optimization_problem.local_slam_pose_translation_weight = 1e5POSE_GRAPH.optimization_problem.local_slam_pose_rotation_weight = 1e5POSE_GRAPH.optimization_problem.odometry_translation_weight = 1e4POSE_GRAPH.optimization_problem.odometry_rotation_weight = 1e4return options

offline_my_robot_2d_localization.lua 主要功能:离线定位测试,仅用单激光雷达,无里程计。

include "offline_my_robot_2d.lua"-- TRAJECTORY_BUILDER.pure_localization_trimmer = {--     max_submaps_to_keep = 3, -- 最大保存子图数,存定位模式通过子图进行定位,但只需要当前和上一个子图即可,我这里设置的是2--   }TRAJECTORY_BUILDER.pure_localization = truePOSE_GRAPH.optimize_every_n_nodes = 20-- output map to base_link for evaluation-- options.provide_odom_frame = false-- POSE_GRAPH.optimization_problem.log_solver_summary = true-- fast localizationMAP_BUILDER.num_background_threads = 8POSE_GRAPH.constraint_builder.sampling_ratio = 0.5 * POSE_GRAPH.constraint_builder.sampling_ratioPOSE_GRAPH.global_sampling_ratio = 0.1 * POSE_GRAPH.global_sampling_ratioPOSE_GRAPH.max_num_final_iterations = 1return options

offline_my_robot_2d.lua 文件功能:离线机器人参数,仅有单线激光雷达。

include "map_builder.lua"include "trajectory_builder.lua"options = {  map_builder = MAP_BUILDER,  trajectory_builder = TRAJECTORY_BUILDER,  map_frame = "map",  tracking_frame = "laser_frame",  published_frame = "laser_frame",  odom_frame = "odom",  provide_odom_frame = false,  publish_frame_projected_to_2d = false,  use_odometry = false,  use_nav_sat = false,  use_landmarks = false,  num_laser_scans = 1,  num_multi_echo_laser_scans = 0,  num_subdivisions_per_laser_scan = 10,  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.,}MAP_BUILDER.use_trajectory_builder_2d = trueTRAJECTORY_BUILDER_2D.num_accumulated_range_data = 4TRAJECTORY_BUILDER_2D.use_imu_data = falsereturn options

my_robot_2d_localization.launch 作用:用实际机器人定位

my_robot_2d.launch 作用:用实际机器人建图

offline_my_robot_2d.launch 作用:用离线的rosbag数据包建图(仅有激光雷达数据) 参考启动方式:

roslaunch cartographer_ros offline_my_robot_2d.launch bag_filenames:=~/ws_ros/cartographer/bag_data/b2-2016-04-05-14-44-52.bag

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