机器人编程趣味实践16-同步定位与地图构建（SLAM）

Posted 2021-06-27 zhangrelay

360度激光用于避障，那怎么可以，完全是大材小用啊……

在 Gazebo 模拟器中进行 SLAM 时，可以在虚拟世界中选择或创建各种环境和机器人模型。SLAM 模拟与实际 TurtleBot3 的 SLAM 非常相似。

通过三维环境的键盘遥控和自主避障行驶，已经充分掌握基本使用，下面进入SLAM环节。

效果如下图所示：

本文不含SLAM算法细节，后续博客更新。

基于地图的更酷炫应用可以参考下文：

• 服务型移动机器人如何实现室内路径全覆盖清扫给你一个清爽干净的家

启动模拟世界

准备了三个 Gazebo 环境，但要使用 SLAM 创建地图，建议使用 TurtleBot3 World 或 TurtleBot3 House。
使用以下命令之一加载 Gazebo 环境。在本指令中，将使用 TurtleBot3 World。
请在 burger、waffle、waffle_pi 中为 TURTLEBOT3_MODEL 参数使用正确的关键字。

• 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

如上二选一即可。

运行 SLAM 节点

使用 Ctrl + Alt + T 从远程 PC 打开一个新终端并运行 SLAM 节点。 默认情况下使用 Cartographer SLAM 方法。

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

运行自主避障节点

使用 Ctrl + Alt + T 从远程 PC 打开一个新终端，然后从 PC 运行drive节点。

•  ros2 run turtlebot3_gazebo turtlebot3_drive

运行遥控操作节点

使用 Ctrl + Alt + T 从远程 PC 打开一个新终端，然后从远程 PC 运行远程操作节点。

• ros2 run turtlebot3_teleop teleop_keyboard

保存地图

成功创建地图后，使用 Ctrl + Alt + T 从远程 PC 打开一个新终端并保存地图。

• ros2 run nav2_map_server map_saver_cli -f ~/map

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'),
    ])

 配置文件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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