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机器人编程趣味实践16-同步定位与地图构建（SLAM）

编程
2023-03-31 10:31:35 时间

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：

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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