使用激光雷达RPLIDAR A1/A2与Cartographer算法实现SLAM
一 、在Gazebo仿真环境中实现SLAM
在终端上输入以下命令，来完成cartographer SLAM的Gazebo仿真：
roslaunch mbot_gazebo mbot_laser_nav_gazebo.launch
roslaunch cartographer_ros cartographer_demo_rplidar2.launch
roslaunch mbot_teleop mbot_teleop.launch
通过键盘控制装有激光雷达的小车在仿真环境中运动，激光雷达不断探测周围环境，并通过cartographer算法完成定位与地图构建：
建图完成后，通过以下命令保存地图：
（1）不再接受进一步数据：
rosservice call /finish_trajectory 0
（2）序列化保存其当前状态
rosservice call /write_state "{filename: '${HOME}/Downloads/mymap.pbstream'}"
（3）将pbstream转换为pgm和yaml
rosrun cartographer_ros cartographer_pbstream_to_ros_map -map_filestem=${HOME}/Downloads/mymap -pbstream_filename=${HOME}/Downloads/mymap.pbstream -resolution=0.05
生成对应的pgm和yaml，放于${HOME}/Downloads/mymap目录下：
cartographer_demo_rplidar2.launch文件内容：
这里要注意的是 ：
（1）仿真环境下，参数"/use_sim_time"的值为"true"
（2）参数配置文件为revo_lds2.lua
revo_lds2.lua文件内容：
include "map_builder.lua"
include "trajectory_builder.lua"
options = {
map_builder = MAP_BUILDER,
trajectory_builder = TRAJECTORY_BUILDER,
map_frame = "map",
tracking_frame = "laser_link",
published_frame = "laser_link",
odom_frame = "odom",
provide_odom_frame = true,
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 = 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.,
}
MAP_BUILDER.use_trajectory_builder_2d = true
TRAJECTORY_BUILDER_2D.submaps.num_range_data = 35
TRAJECTORY_BUILDER_2D.min_range = 0.3
TRAJECTORY_BUILDER_2D.max_range = 8.
TRAJECTORY_BUILDER_2D.missing_data_ray_length = 1.
TRAJECTORY_BUILDER_2D.use_imu_data = false
TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true
TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.linear_search_window = 0.1
TRAJECTORY_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 = 1e2
POSE_GRAPH.optimize_every_n_nodes = 35
POSE_GRAPH.constraint_builder.min_score = 0.65
return options
这里要注意的地方是 ：
tracking_frame = “laser_link”,
published_frame = “laser_link”,
即cartographer参数配置文件中的frame_id，要与xacro机器人模型文件中的frame_id匹配。
二、在真实环境中实现SLAM
在终端上输入以下命令，来完成真实环境中的cartographer SLAM：
roslaunch cartographer_ros cartographer_view_slam.launch
launch文件运行后，在真实的环境中移动激光雷达，激光雷达不断探测周围环境，并通过cartographer算法完成定位与地图构建，地图会以一种渐变的形式由浅至深出现，随着激光雷达的移动，建立完成的地图会逐渐呈现为白色：
建图完成后，保存地图，方法不再赘述。
cartographer_view_slam.launch文件内容如下：
cartographer_demo_rplidar3.launch文件内容如下：
这里要注意的是 ：
（1）非仿真环境下，参数"/use_sim_time"的值为"false"
（2）参数配置文件为revo_lds3.lua
revo_lds3.lua文件内容：
include "map_builder.lua"
include "trajectory_builder.lua"
options = {
map_builder = MAP_BUILDER,
trajectory_builder = TRAJECTORY_BUILDER,
map_frame = "map",
tracking_frame = "laser",
published_frame = "laser",
odom_frame = "odom",
provide_odom_frame = true, --算法内部提供里程计
publish_frame_projected_to_2d = false,
use_odometry = false, --不使用里程计
use_nav_sat = false,
use_landmarks = false,
num_laser_scans = 1,
num_multi_echo_laser_scans = 0,
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.,
}
MAP_BUILDER.use_trajectory_builder_2d = true
TRAJECTORY_BUILDER_2D.submaps.num_range_data = 35
TRAJECTORY_BUILDER_2D.min_range = 0.3
TRAJECTORY_BUILDER_2D.max_range = 5.
TRAJECTORY_BUILDER_2D.missing_data_ray_length = 1.
TRAJECTORY_BUILDER_2D.use_imu_data = false
TRAJECTORY_BUILDER_2D.imu_gravity_time_constant = 9.8
TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true
TRAJECTORY_BUILDER_2D.real_time_correlative_scan_matcher.linear_search_window = 0.1
TRAJECTORY_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 = 1e2
POSE_GRAPH.optimize_every_n_nodes = 35
POSE_GRAPH.constraint_builder.min_score = 0.65
return options
这里要注意的地方是 ：
tracking_frame = “laser”,
published_frame = “laser”,
即cartographer参数配置文件中的frame_id，要与rplidar.launch文件中的frame_id匹配:
