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Interesting practice of robot programming 16 synchronous positioning and map building (SLAM)

2022-07-05 01:28:00 【zhangrelay】

360 Laser is used to avoid obstacles , How can that be? , It's totally overqualified ……

stay Gazebo In the simulator SLAM when , Various environments and robot models can be selected or created in the virtual world .SLAM Simulation and Practice TurtleBot3 Of SLAM Very similar .

Through the three-dimensional environment of the keyboard remote control and autonomous obstacle avoidance driving , Have fully mastered the basic use of , Next entry SLAM link .

The effect is shown below ：

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Synchronous positioning and map building

This article does not contain SLAM Algorithm details , Follow up blog updates .

For more cool applications based on maps, please refer to the following ：

How to achieve full coverage of indoor path cleaning by service-oriented mobile robot to give you a fresh and clean home

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Interesting practice _02

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Interesting practice _03

Start the simulation world

There are three Gazebo Environmental Science , But to use SLAM Create map , It is recommended to use TurtleBot3 World or TurtleBot3 House.

Use one of the following commands to load Gazebo Environmental Science . In this directive , Will use TurtleBot3 World.

Please be there. burger、waffle、waffle_pi In Chinese, it means TURTLEBOT3_MODEL Parameters use the correct keywords .

world
$ export TURTLEBOT3_MODEL=burger
$ ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py
house
$ export TURTLEBOT3_MODEL=burger
$ ros2 launch turtlebot3_gazebo turtlebot3_house.launch.py

Choose one of the two above .

function SLAM node

Use Ctrl + Alt + T From remote PC Open a new terminal and run SLAM node . By default Cartographer SLAM Method .

$ export TURTLEBOT3_MODEL=burger
$ ros2 launch turtlebot3_cartographer cartographer.launch.py use_sim_time:=True

Run the autonomous obstacle avoidance node

Use Ctrl + Alt + T From remote PC Open a new terminal , And then from PC function drive node .

ros2 run turtlebot3_gazebo turtlebot3_drive

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Robot programming _04

Run the remote control operation node
Use Ctrl + Alt + T From remote PC Open a new terminal , And then from the remote PC Run the remote operation node .
ros2 run turtlebot3_teleop teleop_keyboard

Save the map

After successfully creating the map , Use Ctrl + Alt + T From remote PC Open a new terminal and save the map .

ros2 run nav2_map_server map_saver_cli -f ~/map

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Robot programming _05

Interesting practice of robot programming 16- Synchronous positioning and map building （SLAM）_ Synchronous positioning and map building _06

cartographer.launch

       
        import os
        
from ament_index_python.packages import get_package_share_directory
        
from launch import LaunchDescription
        
from launch.actions import DeclareLaunchArgument
        
from launch_ros.actions import Node
        
from launch.substitutions import LaunchConfiguration
        
from launch.actions import IncludeLaunchDescription
        
from launch.launch_description_sources import PythonLaunchDescriptionSource
        
from launch.substitutions import ThisLaunchFileDir
        

        

        
def generate_launch_description():
        
    use_sim_time = LaunchConfiguration('use_sim_time', default='false')
        
    turtlebot3_cartographer_prefix = get_package_share_directory('turtlebot3_cartographer')
        
    cartographer_config_dir = LaunchConfiguration('cartographer_config_dir', default=os.path.join(
        
                                                  turtlebot3_cartographer_prefix, 'config'))
        
    configuration_basename = LaunchConfiguration('configuration_basename',
        
                                                 default='turtlebot3_lds_2d.lua')
        

        
    resolution = LaunchConfiguration('resolution', default='0.05')
        
    publish_period_sec = LaunchConfiguration('publish_period_sec', default='1.0')
        

        
    rviz_config_dir = os.path.join(get_package_share_directory('turtlebot3_cartographer'),
        
                                   'rviz', 'tb3_cartographer.rviz')
        

        
    return LaunchDescription([
        
        DeclareLaunchArgument(
        
            'cartographer_config_dir',
        
            default_value=cartographer_config_dir,
        
            description='Full path to config file to load'),
        
        DeclareLaunchArgument(
        
            'configuration_basename',
        
            default_value=configuration_basename,
        
            description='Name of lua file for cartographer'),
        
        DeclareLaunchArgument(
        
            'use_sim_time',
        
            default_value='false',
        
            description='Use simulation (Gazebo) clock if true'),
        

        
        Node(
        
            package='cartographer_ros',
        
            executable='cartographer_node',
        
            name='cartographer_node',
        
            output='screen',
        
            parameters=[{'use_sim_time': use_sim_time}],
        
            arguments=['-configuration_directory', cartographer_config_dir,
        
                       '-configuration_basename', configuration_basename]),
        

        
        DeclareLaunchArgument(
        
            'resolution',
        
            default_value=resolution,
        
            description='Resolution of a grid cell in the published occupancy grid'),
        

        
        DeclareLaunchArgument(
        
            'publish_period_sec',
        
            default_value=publish_period_sec,
        
            description='OccupancyGrid publishing period'),
        

        
        IncludeLaunchDescription(
        
            PythonLaunchDescriptionSource([ThisLaunchFileDir(), '/occupancy_grid.launch.py']),
        
            launch_arguments={'use_sim_time': use_sim_time, 'resolution': resolution,
        
                              'publish_period_sec': publish_period_sec}.items(),
        
        ),
        

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

       
        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 = "odom",
        
  odom_frame = "odom",
        
  provide_odom_frame = false,
        
  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 = 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.min_range = 0.12
        
TRAJECTORY_BUILDER_2D.max_range = 3.5
        
TRAJECTORY_BUILDER_2D.missing_data_ray_length = 3.
        
TRAJECTORY_BUILDER_2D.use_imu_data = false
        
TRAJECTORY_BUILDER_2D.use_online_correlative_scan_matching = true 
        
TRAJECTORY_BUILDER_2D.motion_filter.max_angle_radians = math.rad(0.1)
        

        
POSE_GRAPH.constraint_builder.min_score = 0.65
        
POSE_GRAPH.constraint_builder.global_localization_min_score = 0.7
        

        
-- POSE_GRAPH.optimize_every_n_nodes = 0
        

        
return options
       
       
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