Robot Navigation with Navigation2 (Physical Robot)

Preparation Work

1. physical object
2. Already ran through robot navigation Navigation2 (Simulation) once.
3. This chapter only covers the general implementation approach. Generally, once you understand the simulation section, reading through the main ideas of the physical section will be enough to grasp how to implement it.
4. This chapter is not from Zhao Xuzuo's tutorial; it is my own implementation approach, provided for reference only. Teacher Zhao may have a better method, but he hasn't released the hardware section tutorial yet.
5. This chapter uses a 4-wheel Mecanum wheel implementation, for reference only.

All of the code below is in this GitHub repository:

https://github.com/CyberNaviRobot/CyberRobot\_ROS2\_WS

The tutorials below only include implementation ideas and won't include source code, so it's recommended to clone this repository and check the source code.

Navigation Parameter Reference

https://docs.nav2.org/configuration/index.html

SLAM localization and mapping

slam_toolbox

Based on the node description above, we need to subscribe to /scan and /tf.

Generally, LiDAR manuals provide source code for publishing /scan, so please refer to your hardware's manual for this.

/tf requires us to publish the transformation from odom_frame to base_frame. We must use C++ code to dynamically publish the coordinate transformation for odom.

However, here you need to publish /odom in order to know the robot's position and orientation, so that the robot's location in the map can be inferred.

Ensure that all parameters of the SLAM Toolbox are set correctly, especially the coordinate systems and similar settings. Other parameters can be fine-tuned according to the documentation.

Ensure the topic published by the LiDAR is /scan.

First, start the LiDAR.

Restart the URDF model and publish TF at the same time.

Finally, start SLAM.

ros2 launch mycar_slam_slam_toolbox online_sync_launch.py use_sim_time:=false

cartographer

According to the Cartographer documentation, we only need /scan and /odom.

First, open the serial port receiving node to receive data transmitted from the STM32.

Then open the odometry node and publish the odom topic.

Publish TF again. You can directly use launch to start robot_state_publisher and joint_state_publisher, and open the URDF model to publish TF.

Start the LiDAR node and publish the scan topic.

After /odom, /scan, and TF are all published, open Cartographer for mapping, then check whether the TF for map has been published.

Check the TF tree as follows:

The mapping is as follows

Map service

Save the map (serialization)

mkdir ./map
ros2 run nav2_map_server map_saver_cli -f map/my_map

Read the map (deserialization)

ros2 launch mycar_map_server map_server.launch.py

AMCL Adaptive Monte Carlo Localization

First, map data is needed to publish the /map topic.

Second, LiDAR data is needed, specifically the /scan topic.

Then a coordinate transform message is needed, specifically the /tf topic.

Then the /initial_pose topic is the initial position on the 2D map. It can be published using rviz2 or via C++ code.

Then you need to modify the parameters:

This is the official website for the parameter:

https://docs.nav2.org/configuration/packages/configuring-amcl.html#

After modifying the Launch, then modify the params parameters.

Here, OmniChassis refers not only to omnidirectional wheel chassis, but to the broader category of omnidirectional wheel chassis — for example, both omnidirectional wheel chassis and Mecanum wheel chassis fall under this category. Of course, you can also define custom chassis types.

Set use_sim_time to False at the top of this configuration file.

Navigation Server

There are too many topics involved, so we've listed them in a table:

1. Subscribed topics

2. Published topics

Since Zhao Xuzuo rewrote the official source code into the workspace, this can be cumbersome for beginners. For beginners, it is recommended to use the official bringup node. Below is a summary of the usage method based on the official Wiki: (Here, the official bringup node is chosen instead of Teacher Zhao Xuzuo's node.)

Below is the configured nav2.launch.py file:

import os

from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration

# from launch_ros.actions import Node

def generate_launch_description():
    navigation2_dir = get_package_share_directory('nav05_navigation2')
    nav2_bringup_dir = get_package_share_directory('nav2_bringup')

    # launch的参数的优先级比yaml的参数优先级高
    use_sim_time = LaunchConfiguration('use_sim_time', default='flase')
    map_yaml_path = LaunchConfiguration('map',default=os.path.join(navigation2_dir,'map','house.yaml'))
    nav2_param_path = LaunchConfiguration('params_file',default=os.path.join(navigation2_dir,'params','nav2.yaml'))

    return LaunchDescription([
        DeclareLaunchArgument('use_sim_time',default_value=use_sim_time,description='Use simulation (Gazebo) clock if true'),
        DeclareLaunchArgument('map',default_value=map_yaml_path,description='Full path to map file to load'),
        DeclareLaunchArgument('params_file',default_value=nav2_param_path,description='Full path to param file to load'),

        IncludeLaunchDescription(
            PythonLaunchDescriptionSource([nav2_bringup_dir,'/launch','/bringup_launch.py']),
            launch_arguments={
                'map': map_yaml_path,
                'use_sim_time': use_sim_time,
                'params_file': nav2_param_path}.items(),
        ),
    ])

Here is rviz2.launch.py:

import os

from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import Node

def generate_launch_description():
    navigation2_dir = get_package_share_directory('nav05_navigation2')

    use_sim_time = LaunchConfiguration('use_sim_time', default='false')

    rviz_config_dir = os.path.join(navigation2_dir,'rviz','nav2.rviz')

    return LaunchDescription([
        DeclareLaunchArgument('use_sim_time',default_value=use_sim_time,description='Use simulation (Gazebo) clock if true'),

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

Below is the nav2.yaml configuration file (differential drive model + DWE local planner):

amcl:
  ros__parameters:
    use_sim_time: false
    alpha1: 0.2
    alpha2: 0.2
    alpha3: 0.2
    alpha4: 0.2
    alpha5: 0.2
    base_frame_id: "base_link"
    beam_skip_distance: 0.5
    beam_skip_error_threshold: 0.9
    beam_skip_threshold: 0.3
    do_beamskip: false
    global_frame_id: "map"
    lambda_short: 0.1
    laser_likelihood_max_dist: 2.0
    laser_max_range: 100.0
    laser_min_range: -1.0
    laser_model_type: "likelihood_field"
    max_beams: 60
    max_particles: 2000
    min_particles: 500
    odom_frame_id: "odom"
    pf_err: 0.05
    pf_z: 0.99
    recovery_alpha_fast: 0.0
    recovery_alpha_slow: 0.0
    resample_interval: 1
    robot_model_type: "nav2_amcl::DifferentialMotionModel"
    save_pose_rate: 0.5
    sigma_hit: 0.2
    tf_broadcast: true
    transform_tolerance: 1.0
    update_min_a: 0.2
    update_min_d: 0.25
    z_hit: 0.5
    z_max: 0.05
    z_rand: 0.5
    z_short: 0.05
    scan_topic: scan

amcl_map_client:
  ros__parameters:
    use_sim_time: false

amcl_rclcpp_node:
  ros__parameters:
    use_sim_time: false

bt_navigator:
  ros__parameters:
    use_sim_time: false
    global_frame: map
    robot_base_frame: base_link
    odom_topic: /odom
    bt_loop_duration: 10
    default_server_timeout: 20

    # 'default_nav_through_poses_bt_xml' and 'default_nav_to_pose_bt_xml' are use defaults:

    # nav2_bt_navigator/navigate_to_pose_w_replanning_and_recovery.xml

    # nav2_bt_navigator/navigate_through_poses_w_replanning_and_recovery.xml

    # They can be set here or via a RewrittenYaml remap from a parent launch file to Nav2.
    plugin_lib_names:
    - nav2_compute_path_to_pose_action_bt_node
    - nav2_compute_path_through_poses_action_bt_node
    - nav2_smooth_path_action_bt_node
    - nav2_follow_path_action_bt_node
    - nav2_spin_action_bt_node
    - nav2_wait_action_bt_node
    - nav2_back_up_action_bt_node
    - nav2_drive_on_heading_bt_node
    - nav2_clear_costmap_service_bt_node
    - nav2_is_stuck_condition_bt_node
    - nav2_goal_reached_condition_bt_node
    - nav2_goal_updated_condition_bt_node
    - nav2_globally_updated_goal_condition_bt_node
    - nav2_is_path_valid_condition_bt_node
    - nav2_initial_pose_received_condition_bt_node
    - nav2_reinitialize_global_localization_service_bt_node
    - nav2_rate_controller_bt_node
    - nav2_distance_controller_bt_node
    - nav2_speed_controller_bt_node
    - nav2_truncate_path_action_bt_node
    - nav2_truncate_path_local_action_bt_node
    - nav2_goal_updater_node_bt_node
    - nav2_recovery_node_bt_node
    - nav2_pipeline_sequence_bt_node
    - nav2_round_robin_node_bt_node
    - nav2_transform_available_condition_bt_node
    - nav2_time_expired_condition_bt_node
    - nav2_path_expiring_timer_condition
    - nav2_distance_traveled_condition_bt_node
    - nav2_single_trigger_bt_node
    - nav2_is_battery_low_condition_bt_node
    - nav2_navigate_through_poses_action_bt_node
    - nav2_navigate_to_pose_action_bt_node
    - nav2_remove_passed_goals_action_bt_node
    - nav2_planner_selector_bt_node
    - nav2_controller_selector_bt_node
    - nav2_goal_checker_selector_bt_node
    - nav2_controller_cancel_bt_node
    - nav2_path_longer_on_approach_bt_node
    - nav2_wait_cancel_bt_node
    - nav2_spin_cancel_bt_node
    - nav2_back_up_cancel_bt_node
    - nav2_drive_on_heading_cancel_bt_node

bt_navigator_rclcpp_node:
  ros__parameters:
    use_sim_time: false

controller_server:
  ros__parameters:
    use_sim_time: false
    controller_frequency: 20.0
    min_x_velocity_threshold: 0.001
    min_y_velocity_threshold: 0.5
    min_theta_velocity_threshold: 0.001
    failure_tolerance: 0.3
    progress_checker_plugin: "progress_checker"
    goal_checker_plugins: ["general_goal_checker"] # "precise_goal_checker"
    controller_plugins: ["FollowPath"]

    # Progress checker parameters
    progress_checker:
      plugin: "nav2_controller::SimpleProgressChecker"
      required_movement_radius: 0.5
      movement_time_allowance: 10.0

    # Goal checker parameters
    #precise_goal_checker:

    #  plugin: "nav2_controller::SimpleGoalChecker"

    #  xy_goal_tolerance: 0.25

    #  yaw_goal_tolerance: 0.25

    #  stateful: True
    general_goal_checker:
      stateful: True
      plugin: "nav2_controller::SimpleGoalChecker"
      xy_goal_tolerance: 0.25
      yaw_goal_tolerance: 0.25

    # DWB parameters
    FollowPath:
      plugin: "dwb_core::DWBLocalPlanner"
      debug_trajectory_details: True
      min_vel_x: 0.0
      min_vel_y: 0.0
      max_vel_x: 0.26
      max_vel_y: 0.0
      max_vel_theta: 1.0
      min_speed_xy: 0.0
      max_speed_xy: 0.26
      min_speed_theta: 0.0

      # Add high threshold velocity for turtlebot 3 issue.

      # https://github.com/ROBOTIS-GIT/turtlebot3_simulations/issues/75
      acc_lim_x: 2.5
      acc_lim_y: 0.0
      acc_lim_theta: 3.2
      decel_lim_x: -2.5
      decel_lim_y: 0.0
      decel_lim_theta: -3.2
      vx_samples: 20
      vy_samples: 5
      vtheta_samples: 20
      sim_time: 1.7
      linear_granularity: 0.05
      angular_granularity: 0.025
      transform_tolerance: 0.2
      xy_goal_tolerance: 0.25
      trans_stopped_velocity: 0.25
      short_circuit_trajectory_evaluation: True
      stateful: True
      critics: ["RotateToGoal", "Oscillation", "BaseObstacle", "GoalAlign", "PathAlign", "PathDist", "GoalDist"]
      BaseObstacle.scale: 0.02
      PathAlign.scale: 32.0
      PathAlign.forward_point_distance: 0.1
      GoalAlign.scale: 24.0
      GoalAlign.forward_point_distance: 0.1
      PathDist.scale: 32.0
      GoalDist.scale: 24.0
      RotateToGoal.scale: 32.0
      RotateToGoal.slowing_factor: 5.0
      RotateToGoal.lookahead_time: -1.0

controller_server_rclcpp_node:
  ros__parameters:
    use_sim_time: false

local_costmap:
  local_costmap:
    ros__parameters:
      update_frequency: 5.0
      publish_frequency: 2.0
      global_frame: odom
      robot_base_frame: base_link
      use_sim_time: false
      rolling_window: true
      width: 3
      height: 3
      resolution: 0.05
      robot_radius: 0.22
      plugins: ["static_layer", "obstacle_layer", "voxel_layer", "inflation_layer"]
      inflation_layer:
        plugin: "nav2_costmap_2d::InflationLayer"
        cost_scaling_factor: 3.0
        inflation_radius: 0.55
      obstacle_layer:
        plugin: "nav2_costmap_2d::ObstacleLayer"
        enabled: True
        observation_sources: scan
        scan:
          topic: /scan
          max_obstacle_height: 2.0
          clearing: True
          marking: True
          data_type: "LaserScan"
          raytrace_max_range: 3.0
          raytrace_min_range: 0.0
          obstacle_max_range: 2.5
          obstacle_min_range: 0.0
      voxel_layer:
        plugin: "nav2_costmap_2d::VoxelLayer"
        enabled: True
        publish_voxel_map: True
        origin_z: 0.0
        z_resolution: 0.05
        z_voxels: 16
        max_obstacle_height: 2.0
        mark_threshold: 0
        observation_sources: scan
        scan:
          topic: /scan
          max_obstacle_height: 2.0
          clearing: True
          marking: True
          data_type: "LaserScan"
          raytrace_max_range: 3.0
          raytrace_min_range: 0.0
          obstacle_max_range: 2.5
          obstacle_min_range: 0.0
      static_layer:
        plugin: "nav2_costmap_2d::StaticLayer"
        map_subscribe_transient_local: True
      always_send_full_costmap: True

  local_costmap_client:
    ros__parameters:
      use_sim_time: false
  local_costmap_rclcpp_node:
    ros__parameters:
      use_sim_time: false

global_costmap:
  global_costmap:
    ros__parameters:
      update_frequency: 1.0
      publish_frequency: 1.0
      global_frame: map
      robot_base_frame: base_link
      use_sim_time: false
      robot_radius: 0.22
      resolution: 0.05
      track_unknown_space: true
      plugins: ["static_layer", "obstacle_layer", "inflation_layer"]
      obstacle_layer:
        plugin: "nav2_costmap_2d::ObstacleLayer"
        enabled: True
        observation_sources: scan
        scan:
          topic: /scan
          max_obstacle_height: 2.0
          clearing: True
          marking: True
          data_type: "LaserScan"
          raytrace_max_range: 3.0
          raytrace_min_range: 0.0
          obstacle_max_range: 2.5
          obstacle_min_range: 0.0
      static_layer:
        plugin: "nav2_costmap_2d::StaticLayer"
        map_subscribe_transient_local: True
      inflation_layer:
        plugin: "nav2_costmap_2d::InflationLayer"
        cost_scaling_factor: 3.0
        inflation_radius: 0.55
      always_send_full_costmap: True

  global_costmap_client:
    ros__parameters:
      use_sim_time: false
  global_costmap_rclcpp_node:
    ros__parameters:
      use_sim_time: false

map_server:
  ros__parameters:
    use_sim_time: false
    yaml_filename: "house.yaml"

map_saver:
  ros__parameters:
    use_sim_time: false
    save_map_timeout: 5.0
    free_thresh_default: 0.25
    occupied_thresh_default: 0.65
    map_subscribe_transient_local: True

planner_server:
  ros__parameters:
    expected_planner_frequency: 20.0
    use_sim_time: false
    planner_plugins: ["GridBased"]
    GridBased:
      plugin: "nav2_navfn_planner/NavfnPlanner"
      tolerance: 0.5
      use_astar: false
      allow_unknown: true

planner_server_rclcpp_node:
  ros__parameters:
    use_sim_time: false

smoother_server:
  ros__parameters:
    use_sim_time: false
    smoother_plugins: ["simple_smoother"]
    simple_smoother:
      plugin: "nav2_smoother::SimpleSmoother"
      tolerance: 1.0e-10
      max_its: 1000
      do_refinement: True

behavior_server:
  ros__parameters:
    costmap_topic: local_costmap/costmap_raw
    footprint_topic: local_costmap/published_footprint
    cycle_frequency: 10.0
    behavior_plugins: ["spin", "backup", "drive_on_heading", "wait"]
    spin:
      plugin: "nav2_behaviors/Spin"
    backup:
      plugin: "nav2_behaviors/BackUp"
    drive_on_heading:
      plugin: "nav2_behaviors/DriveOnHeading"
    wait:
      plugin: "nav2_behaviors/Wait"
    global_frame: odom
    robot_base_frame: base_link
    transform_tolerance: 0.1
    use_sim_time: false
    simulate_ahead_time: 2.0
    max_rotational_vel: 1.0
    min_rotational_vel: 0.4
    rotational_acc_lim: 3.2

robot_state_publisher:
  ros__parameters:
    use_sim_time: false

waypoint_follower:
  ros__parameters:
    loop_rate: 20
    stop_on_failure: false
    waypoint_task_executor_plugin: "wait_at_waypoint"
    wait_at_waypoint:
      plugin: "nav2_waypoint_follower::WaitAtWaypoint"
      enabled: True
      waypoint_pause_duration: 200

velocity_smoother:
  ros__parameters:
    use_sim_time: false
    smoothing_frequency: 20.0
    scale_velocities: False
    feedback: "OPEN_LOOP"
    max_velocity: [0.26, 0.0, 1.0]
    min_velocity: [-0.26, 0.0, -1.0]
    max_accel: [2.5, 0.0, 3.2]
    max_decel: [-2.5, 0.0, -3.2]
    odom_topic: "odom"
    odom_duration: 0.1
    deadband_velocity: [0.0, 0.0, 0.0]
    velocity_timeout: 1.0

Multi-vehicle formation