機器人導航Navigation2(實體篇)
準備工作
- 實物
- 已經跑過一遍機器人導航Navigation2(仿真篇)
- 本章只講大體思路實現,一般只要你仿真篇搞明白了,實體篇看看大體思路就懂怎麼實現了。
- 本章非趙虛左教程,是自己的實現思路,僅供參考,可能趙老師有更好的辦法,不過他還沒出實體篇教程。
- 本章用的是4輪麥克納姆輪實現的,僅供參考。
以下代碼都在下方這個github倉庫裏:
https://github.com/CyberNaviRobot/CyberRobot\_ROS2\_WS
下方的教程只有實現思路,不會放源碼,所以建議克隆一下這個倉庫,看看源碼。
導航參數參考
https://docs.nav2.org/configuration/index.html
SLAM 定位與建圖
slam_toolbox
根據上方的節點說明,我們要訂閱/scan和/tf。
一般激光雷達的說明書都會提供源碼去發佈/scan,所以這個請看你硬件的說明書。
/tf則需要我們發佈odom_frame到base_frame的轉換,我們必須使用C++代碼去動態發佈odom的座標變換。
但是這裏你需要發佈/odom,以便於知道機器人的位置和姿態,這樣才能夠夠推算出機器人在map中的位置。

確保slam toolbox各項參數沒有設置錯,特別是座標系等等,其他參數可以看着說明微調。

確保激光雷達發佈的話題是/scan。

先啓動激光雷達

再啓動urdf模型,同時發佈tf。

最後開啓slam
ros2 launch mycar_slam_slam_toolbox online_sync_launch.py use_sim_time:=false



cartographer
根據cartographer說明,我們需要/scan和/odom即可。
先打開串口接收節點,接收stm32傳過來的數據。

然後再打開里程計節點,發佈odom話題


再發布一下TF,可以直接用launch開啓robot_state_publisher和joint_state_publisher,並打開urdf模型來發布TF。

打開激光雷達的節點,發佈scan話題

等/odom,/scan和TF全發了之後,再打開cartographer建圖,然後可以檢查map的TF是否發佈。

檢查TF樹如下:

建圖如下


地圖服務
保存地圖(序列化)
mkdir ./map
ros2 run nav2_map_server map_saver_cli -f map/my_map


讀取地圖(反序列化)

ros2 launch mycar_map_server map_server.launch.py
AMCL自適應蒙特卡洛定位
首先需要地圖的數據,發佈/map話題。
其次需要激光雷達數據,即/scan話題。
然後需要座標變換消息,即/tf話題。
然後那個/initial_pose話題,是2D地圖上的初始位置,可以用rviz2發佈,也可以用C++代碼發佈。

然後需要修改一下參數:
這個是參數的官方網站:
https://docs.nav2.org/configuration/packages/configuring-amcl.html#

修改完Launch後,再修改params參數。

這裏的OmniChassis不止指全向輪底盤,而是廣義的全向輪底盤,像全向輪底盤,麥輪底盤都是全向輪底盤。當然也可以自定義底盤類型。
這個配置文件最頂上的那個use_sim_time設置爲False。





導航服務器
涉及的話題太多了,所以我們列出來了一個表:
- 訂閱的話題
| 話題 | 接口 | 描述 |
|---|---|---|
| /goal_pose | geometry_msgs/msg/PoseStamped | 導航目標點,用於觸發導航任務 |
| /tf | tf2_msgs/msg/TFMessage | 座標變換消息,用於不同座標系之間的轉換 |
| /odom | nav_msgs/msg/Odometry | 里程計數據,提供機器人位置和運動信息 |
| 話題 | 接口 | 描述 |
| /global_costmap/footprint | geometry_msgs/msg/Polygon | 機器人(或任何移動平臺)的足跡(footprint)信息。足跡是機器人在地圖上佔據的空間形狀,通常用多邊形表示。 |
| /map | nav_msgs/msg/OccupancyGrid | 發佈環境地圖,特別是用於導航的佔用網格圖(Occupancy Grid Map)。 |
| /scan | sensor_msgs/msg/LaserScan | 激光掃描數據。 |
| 話題 | 接口 | 描述 |
| /odom | nav_msgs/msg/Odometry | 機器人的里程計信息,包含位置、速度和姿態 |
| /speed_limit | nav2_msgs/msg/SpeedLimit | 導航過程中的速度限制信息,用於動態調整機器人的移動速度 |
| 話題 | 接口 | 描述 |
| /local_costmap/footprint | geometry_msgs/msg/Polygon | 機器人或移動平臺的足跡多邊形,用於本地代價地圖的計算 |
| /scan | sensor_msgs/msg/LaserScan | 激光掃描儀的掃描數據,用於環境感知和避障 |
| 話題 | 接口 | 描述 |
| /clock | rosgraph_msgs/msg/Clock | ROS系統時間 |
| /cmd_vel_teleop | geometry_msgs/msg/Twist | 遙操作命令,用於控制機器人的線性和角速度 |
| /local_costmap/costmap_raw | nav2_msgs/msg/Costmap | 局部代價地圖的原始數據 |
| /local_costmap/published_footprint | geometry_msgs/msg/PolygonStamped | 機器人在局部代價地圖中的已發佈足跡 |
| /preempt_teleop | std_msgs/msg/Empty | 遙操作搶佔信號,用於中斷當前遙操作 |
| 話題 | 接口 | 描述 |
| /global_costmap/costmap_raw | nav2_msgs/msg/Costmap | 全局代價地圖的原始數據,用於路徑規劃 |
| /global_costmap/published_footprint | geometry_msgs/msg/PolygonStamped | 機器人在全局代價地圖中的足跡表示 |
| 話題 | 接口 | 描述 |
| /cmd_vel_nav | geometry_msgs/msg/Twist | 接收來自其他節點的速度控制指令的話題 |
- 發佈的話題
| 話題 | 接口 | 描述 |
|---|---|---|
| /plan | nav_msgs/msg/Path | 當前位置到目標點的全局路徑 |
| 話題 | 接口 | 描述 |
| /global_costmap/costmap | nav_msgs/msg/OccupancyGrid | 發佈全局代價地圖的當前狀態。 |
| /global_costmap/costmap_raw | nav2_msgs/msg/Costmap | 未經進一步處理的原始代價地圖數據。 |
| /global_costmap/costmap_updates | map_msgs/msg/OccupancyGridUpdate | 全局代價地圖的更新,該消息可以高效更新地圖。 |
| /global_costmap/published_footprint | geometry_msgs/msg/PolygonStamped | 發佈機器人的足跡(footprint),即機器人在地圖上佔據的空間形狀。 |
| 話題名稱 | 消息類型 | 描述 |
| /cmd_vel_nav | geometry_msgs/msg/Twist | 發佈控制命令,包括線性和角速度,用於控制機器人按照規劃路徑移動。 |
| /cost_cloud | sensor_msgs/msg/PointCloud2 | 發佈成本地圖中的點雲數據,用於避障和路徑規劃。 |
| /local_plan | nav_msgs/msg/Path | 發佈局部路徑規劃結果,即機器人應如何到達當前目標點附近的一個點。 |
| /marker | visualization_msgs/msg/MarkerArray | 發佈可視化標記,用於在RViz等可視化工具中顯示路徑、障礙物等信息。 |
| /received_global_plan | nav_msgs/msg/Path | 發佈從全局規劃器接收到的全局路徑,即當前位置到目標點的路徑。 |
| /transformed_global_plan | nav_msgs/msg/Path | 發佈經過座標變換的全局路徑,確保路徑與機器人的當前座標系一致。 |
| 話題 | 接口 | 描述 |
| /local_costmap/clearing_endpoints | sensor_msgs/msg/PointCloud2 | 清除成本圖上的障礙物點雲數據,通常用於動態障礙物處理 |
| /local_costmap/costmap | nav_msgs/msg/OccupancyGrid | 本地成本圖,表示機器人周圍環境的可通行性 |
| /local_costmap/costmap_raw | nav2_msgs/msg/Costmap | 未經處理的本地成本圖,可能包含更詳細的信息 |
| /local_costmap/costmap_updates | map_msgs/msg/OccupancyGridUpdate | 本地成本圖的更新信息,包括哪些區域發生了變化 |
| /local_costmap/published_footprint | geometry_msgs/msg/PolygonStamped | 發佈的機器人足跡多邊形,時間戳表示發佈時間 |
| /local_costmap/voxel_grid | nav2_msgs/msg/VoxelGrid | 體素網格數據,用於成本圖生成中的空間劃分和優化 |
| 話題 | 接口 | 描述 |
| /cmd_vel | geometry_msgs/msg/Twist | 發送給底層控制器的速度命令 |
| 話題 | 接口 | 描述 |
| /plan_smoothed | nav_msgs/msg/Path | 經過平滑處理後的全局路徑 |
| 話題 | 接口 | 描述 |
| /cmd_vel | geometry_msgs/msg/Twist | 發佈經過處理或平滑後的速度控制指令的話題 |
由於趙虛左是把官方的源碼重新寫在了WS裏,這樣對於初學者來說會比較麻煩,對於初學者來說建議使用官方寫好的bringup節點,以下是我根據官方Wiki總結出來的使用方法:(這裏選擇使用官方的bringup節點,而不是趙虛左老師的節點。)
以下是配置的nav2.launch.py文件:
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(),
),
])
以下是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'),
])
以下是nav2.yaml配置文件(差速模型+DWE局部規劃器):
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