Get nav2 running in simulation

This commit is contained in:
Matt Spencer
2026-08-01 13:55:36 +00:00
parent 44e039beac
commit 7e1cad1536
12 changed files with 921 additions and 10 deletions
@@ -7,13 +7,67 @@
controller_manager inside gz-sim and reads the controller yaml. controller_manager inside gz-sim and reads the controller yaml.
Per-wheel mecanum friction is emitted by the wheel macro when Per-wheel mecanum friction is emitted by the wheel macro when
gazebo_ignition (sim) is true, so it is NOT repeated here. gazebo_ignition (sim) is true, so it is NOT repeated here.
controllers_file : primary controller params (the AGV base controllers).
controllers_file_extra : OPTIONAL second params file, loaded into the SAME
controller_manager. Used when the AGV is composed
into a larger robot (e.g. a mobile manipulator) so
the additional controllers (e.g. an arm_controller)
share the single gz_ros2_control controller_manager.
Empty by default -> standalone AGV unaffected.
--> -->
<xacro:macro name="agv_pro_gazebo" params="prefix controllers_file"> <xacro:macro name="agv_pro_gazebo" params="prefix controllers_file controllers_file_extra:=''">
<gazebo> <gazebo>
<plugin filename="gz_ros2_control-system" <plugin filename="gz_ros2_control-system"
name="gz_ros2_control::GazeboSimROS2ControlPlugin"> name="gz_ros2_control::GazeboSimROS2ControlPlugin">
<parameters>${controllers_file}</parameters> <parameters>${controllers_file}</parameters>
<xacro:if value="${controllers_file_extra != ''}">
<parameters>${controllers_file_extra}</parameters>
</xacro:if>
</plugin> </plugin>
</gazebo> </gazebo>
<!--
2D lidar sensor on laser_link. Publishes a gz LaserScan on the gz topic
'scan'; gazebo.launch bridges it to the ROS /scan (sensor_msgs/LaserScan)
that Nav2 / SLAM consume. The gz-sim-sensors-system plugin in the world
SDF renders it. gz_frame_id stamps the scan with the laser_link frame so
TF lines up. Mirrors a generic 360deg 2D planar lidar; on the real robot
the physical LSLiDAR/Livox/Unitree driver publishes the same /scan.
-->
<gazebo reference="${prefix}laser_link">
<sensor name="${prefix}lidar" type="gpu_lidar">
<pose>0 0 0 0 0 0</pose>
<topic>scan</topic>
<gz_frame_id>${prefix}laser_link</gz_frame_id>
<update_rate>10</update_rate>
<always_on>1</always_on>
<visualize>true</visualize>
<lidar>
<scan>
<horizontal>
<samples>360</samples>
<resolution>1</resolution>
<min_angle>-3.141592653589793</min_angle>
<max_angle>3.141592653589793</max_angle>
</horizontal>
</scan>
<!--
The front-mounted 360 deg lidar physically sees the robot's own
chassis behind it (returns from ~0.19 m out to ~0.38 m at the rear
angles). Those self-returns are removed downstream by a
laser_filters box filter (see agv_pro_gazebo scan_filter.yaml) in the
base_footprint frame, which keeps full forward/side sensing while
dropping any point inside the chassis outline. Both simulation and
the physical robot run the same filter, so /scan stays identical.
-->
<range>
<min>0.15</min>
<max>12.0</max>
<resolution>0.01</resolution>
</range>
</lidar>
</sensor>
</gazebo>
</xacro:macro> </xacro:macro>
</robot> </robot>
@@ -18,6 +18,13 @@
<xacro:arg name="controllers_file" default="" /> <xacro:arg name="controllers_file" default="" />
<xacro:property name="controllers_file" value="$(arg controllers_file)" /> <xacro:property name="controllers_file" value="$(arg controllers_file)" />
<!-- Optional second controller params file, loaded into the SAME
gz_ros2_control controller_manager. Used when composing the AGV into a
larger robot (e.g. a mobile manipulator) so extra controllers share the
single controller_manager. Empty -> standalone behaviour unchanged. -->
<xacro:arg name="controllers_file_extra" default="" />
<xacro:property name="controllers_file_extra" value="$(arg controllers_file_extra)" />
<link name="${prefix}base_footprint" /> <link name="${prefix}base_footprint" />
<joint name="${prefix}base_joint" type="fixed"> <joint name="${prefix}base_joint" type="fixed">
@@ -146,7 +153,8 @@
<!-- Gazebo system plugin (hosts controller_manager); wheel friction is in the wheel macro --> <!-- Gazebo system plugin (hosts controller_manager); wheel friction is in the wheel macro -->
<xacro:if value="${sim}"> <xacro:if value="${sim}">
<xacro:include filename="$(find agv_pro_description)/urdf/agv_pro.gazebo.xacro" /> <xacro:include filename="$(find agv_pro_description)/urdf/agv_pro.gazebo.xacro" />
<xacro:agv_pro_gazebo prefix="${prefix}" controllers_file="${controllers_file}" /> <xacro:agv_pro_gazebo prefix="${prefix}" controllers_file="${controllers_file}"
controllers_file_extra="${controllers_file_extra}" />
</xacro:if> </xacro:if>
</robot> </robot>
@@ -0,0 +1,30 @@
# laser_filters chain for the AGV Pro 2D lidar.
#
# The 360 deg lidar is mounted at the front of the robot (laser_link is ~0.179 m
# ahead of base_link), so its rearward beams strike the robot's own chassis and
# report returns from ~0.19 m out to ~0.38 m. Left unfiltered, those self-returns
# were baked into the SLAM map and both Nav2 costmaps, marking the robot's own
# cell lethal (cost 253) so the planner refused to plan from an in-collision
# start ("Failed to create plan with tolerance").
#
# The box filter drops any scan point that falls inside the chassis outline
# (expressed in base_footprint), which removes the self-returns while keeping all
# real obstacles in front of and beside the robot. The physical robot runs the
# same filter, so the /scan consumed by SLAM/Nav2 is identical to simulation.
scan_filter_chain:
ros__parameters:
filter1:
name: chassis_box_filter
type: laser_filters/LaserScanBoxFilter
params:
box_frame: base_footprint
# Chassis extent in base_footprint (metres). The laser sits at x=+0.179,
# so the body occupies roughly x in [-0.35, 0.18] and y in [-0.30, 0.30].
min_x: -0.35
max_x: 0.18
min_y: -0.30
max_y: 0.30
min_z: -1.0
max_z: 1.0
# false => remove points that fall INSIDE the box (the chassis).
invert: false
@@ -29,12 +29,13 @@ def generate_launch_description():
# Shared robot description (agv_pro_description) built for simulation. # Shared robot description (agv_pro_description) built for simulation.
xacro_file = os.path.join(pkg_description, 'urdf', 'agv_pro.urdf.xacro') xacro_file = os.path.join(pkg_description, 'urdf', 'agv_pro.urdf.xacro')
controllers_file = os.path.join(pkg_gazebo, 'config', 'agv_control.yaml') controllers_file = os.path.join(pkg_gazebo, 'config', 'agv_control.yaml')
world_file = os.path.join(pkg_gazebo, 'worlds', 'empty.world') default_world = os.path.join(pkg_gazebo, 'worlds', 'empty.world')
rviz_config = os.path.join(pkg_gazebo, 'rviz', 'agvpro_display.rviz') rviz_config = os.path.join(pkg_gazebo, 'rviz', 'agvpro_display.rviz')
use_sim_time = LaunchConfiguration('use_sim_time') use_sim_time = LaunchConfiguration('use_sim_time')
use_rviz = LaunchConfiguration('use_rviz') use_rviz = LaunchConfiguration('use_rviz')
headless = LaunchConfiguration('headless') headless = LaunchConfiguration('headless')
world = LaunchConfiguration('world')
robot_description = { robot_description = {
'robot_description': ParameterValue( 'robot_description': ParameterValue(
@@ -64,9 +65,8 @@ def generate_launch_description():
# Start gz-sim (Gazebo Harmonic) with the world. # Start gz-sim (Gazebo Harmonic) with the world.
# '-s' (server only) is added when headless:=true. # '-s' (server only) is added when headless:=true.
gz_args = PythonExpression([ gz_args = PythonExpression([
"'-r -v4 -s ' + ", repr(world_file), "'-r -v4 -s ' + '", world, "' if '", headless,
" if '", headless, "' == 'true' ", "' == 'true' else '-r -v4 ' + '", world, "'",
"else '-r -v4 ' + ", repr(world_file),
]) ])
gz_sim = IncludeLaunchDescription( gz_sim = IncludeLaunchDescription(
PythonLaunchDescriptionSource( PythonLaunchDescriptionSource(
@@ -104,6 +104,35 @@ def generate_launch_description():
output='screen', output='screen',
) )
# Bridge the 2D lidar: gz LaserScan -> ROS /scan_raw (sensor_msgs/LaserScan).
# The sensor is defined on laser_link in agv_pro.gazebo.xacro. The raw scan
# goes to /scan_raw and is cleaned by the box filter below before Nav2/SLAM
# consume /scan. use_sim_time so the scan stamps use the Gazebo clock.
scan_bridge = Node(
package='ros_gz_bridge',
executable='parameter_bridge',
arguments=['/scan@sensor_msgs/msg/LaserScan[gz.msgs.LaserScan'],
parameters=[{'use_sim_time': use_sim_time}],
remappings=[('/scan', '/scan_raw')],
output='screen',
)
# Remove the robot's own chassis returns from the front-mounted lidar.
# The box filter (config/scan_filter.yaml) drops any point inside the chassis
# outline in base_footprint, publishing the cleaned scan on /scan. Without it
# the self-returns mark the robot's own cell lethal and Nav2 cannot plan.
scan_filter = Node(
package='laser_filters',
executable='scan_to_scan_filter_chain',
name='scan_filter_chain',
parameters=[
os.path.join(pkg_gazebo, 'config', 'scan_filter.yaml'),
{'use_sim_time': use_sim_time},
],
remappings=[('scan', '/scan_raw'), ('scan_filtered', '/scan')],
output='screen',
)
# Controllers (controller_manager runs inside the gz_ros2_control plugin) # Controllers (controller_manager runs inside the gz_ros2_control plugin)
joint_state_broadcaster_spawner = Node( joint_state_broadcaster_spawner = Node(
package='controller_manager', package='controller_manager',
@@ -117,15 +146,20 @@ def generate_launch_description():
# Remap the controller's reference topic (~/reference) to the standard # Remap the controller's reference topic (~/reference) to the standard
# /cmd_vel so teleop and nav2 (which publish geometry_msgs/TwistStamped) # /cmd_vel so teleop and nav2 (which publish geometry_msgs/TwistStamped)
# drive the robot directly. NOTE: the remap key must be the private name # drive the robot directly. Also remap the controller's private odometry
# '~/reference' — a bare 'reference:=/cmd_vel' is silently ignored. # outputs to the global names the rest of the stack expects:
# ~/tf_odometry -> /tf (so odom->base_footprint reaches the TF tree)
# ~/odometry -> /odom (nav2 odom_topic, robot_localization, etc.)
# NOTE: the remap keys must be the private names ('~/...'); a bare
# 'reference:=/cmd_vel' is silently ignored.
mecanum_drive_controller_spawner = Node( mecanum_drive_controller_spawner = Node(
package='controller_manager', package='controller_manager',
executable='spawner', executable='spawner',
arguments=[ arguments=[
'mecanum_drive_controller', 'mecanum_drive_controller',
'--controller-manager', '/controller_manager', '--controller-manager', '/controller_manager',
'--controller-ros-args', '-r ~/reference:=/cmd_vel', '--controller-ros-args',
'-r ~/reference:=/cmd_vel -r ~/tf_odometry:=/tf -r ~/odometry:=/odom',
], ],
output='screen', output='screen',
) )
@@ -156,10 +190,17 @@ def generate_launch_description():
default_value='false', default_value='false',
description='Run gz-sim without the GUI (server only)', description='Run gz-sim without the GUI (server only)',
), ),
DeclareLaunchArgument(
'world',
default_value=default_world,
description='Full path to the Gazebo world (SDF) to load',
),
gz_resource_path, gz_resource_path,
gz_sim, gz_sim,
robot_state_publisher, robot_state_publisher,
clock_bridge, clock_bridge,
scan_bridge,
scan_filter,
delayed_spawn, delayed_spawn,
# Load controllers only after the robot has been spawned # Load controllers only after the robot has been spawned
RegisterEventHandler( RegisterEventHandler(
@@ -18,6 +18,7 @@
<!-- Gazebo (gz-sim Harmonic) integration for ROS 2 Jazzy --> <!-- Gazebo (gz-sim Harmonic) integration for ROS 2 Jazzy -->
<exec_depend>ros_gz_sim</exec_depend> <exec_depend>ros_gz_sim</exec_depend>
<exec_depend>ros_gz_bridge</exec_depend> <exec_depend>ros_gz_bridge</exec_depend>
<exec_depend>laser_filters</exec_depend>
<depend>gz_ros2_control</depend> <depend>gz_ros2_control</depend>
<depend>robot_state_publisher</depend> <depend>robot_state_publisher</depend>
@@ -0,0 +1,133 @@
<?xml version="1.0" ?>
<!--
room.world - a simple enclosed room for testing SLAM and Nav2 in simulation.
Same required gz-sim system plugins as empty.world (physics, scene broadcaster,
user commands, sensors) plus four perimeter walls so the 2D lidar has features
to map and localise against.
-->
<sdf version="1.10">
<world name="room_world">
<plugin filename="gz-sim-physics-system"
name="gz::sim::systems::Physics">
</plugin>
<plugin filename="gz-sim-user-commands-system"
name="gz::sim::systems::UserCommands">
</plugin>
<plugin filename="gz-sim-scene-broadcaster-system"
name="gz::sim::systems::SceneBroadcaster">
</plugin>
<plugin filename="gz-sim-sensors-system"
name="gz::sim::systems::Sensors">
<render_engine>ogre2</render_engine>
</plugin>
<physics name="1ms" type="ignored">
<max_step_size>0.001</max_step_size>
<real_time_factor>1.0</real_time_factor>
</physics>
<light type="directional" name="sun">
<cast_shadows>true</cast_shadows>
<pose>0 0 10 0 0 0</pose>
<diffuse>0.8 0.8 0.8 1</diffuse>
<specular>0.2 0.2 0.2 1</specular>
<attenuation>
<range>1000</range>
<constant>0.9</constant>
<linear>0.01</linear>
<quadratic>0.001</quadratic>
</attenuation>
<direction>-0.5 0.1 -0.9</direction>
</light>
<model name="ground_plane">
<static>true</static>
<link name="link">
<collision name="collision">
<geometry>
<plane><normal>0 0 1</normal><size>100 100</size></plane>
</geometry>
</collision>
<visual name="visual">
<geometry>
<plane><normal>0 0 1</normal><size>100 100</size></plane>
</geometry>
<material>
<ambient>0.8 0.8 0.8 1</ambient>
<diffuse>0.8 0.8 0.8 1</diffuse>
<specular>0.8 0.8 0.8 1</specular>
</material>
</visual>
</link>
</model>
<!-- 8m x 8m room: four walls, 0.1m thick, 1m tall, centred on origin -->
<model name="walls">
<static>true</static>
<link name="link">
<!-- North wall (+X) -->
<collision name="north_col">
<pose>4 0 0.5 0 0 0</pose>
<geometry><box><size>0.1 8 1</size></box></geometry>
</collision>
<visual name="north_vis">
<pose>4 0 0.5 0 0 0</pose>
<geometry><box><size>0.1 8 1</size></box></geometry>
<material><ambient>0.6 0.6 0.65 1</ambient><diffuse>0.6 0.6 0.65 1</diffuse></material>
</visual>
<!-- South wall (-X) -->
<collision name="south_col">
<pose>-4 0 0.5 0 0 0</pose>
<geometry><box><size>0.1 8 1</size></box></geometry>
</collision>
<visual name="south_vis">
<pose>-4 0 0.5 0 0 0</pose>
<geometry><box><size>0.1 8 1</size></box></geometry>
<material><ambient>0.6 0.6 0.65 1</ambient><diffuse>0.6 0.6 0.65 1</diffuse></material>
</visual>
<!-- East wall (+Y) -->
<collision name="east_col">
<pose>0 4 0.5 0 0 0</pose>
<geometry><box><size>8 0.1 1</size></box></geometry>
</collision>
<visual name="east_vis">
<pose>0 4 0.5 0 0 0</pose>
<geometry><box><size>8 0.1 1</size></box></geometry>
<material><ambient>0.6 0.6 0.65 1</ambient><diffuse>0.6 0.6 0.65 1</diffuse></material>
</visual>
<!-- West wall (-Y) -->
<collision name="west_col">
<pose>0 -4 0.5 0 0 0</pose>
<geometry><box><size>8 0.1 1</size></box></geometry>
</collision>
<visual name="west_vis">
<pose>0 -4 0.5 0 0 0</pose>
<geometry><box><size>8 0.1 1</size></box></geometry>
<material><ambient>0.6 0.6 0.65 1</ambient><diffuse>0.6 0.6 0.65 1</diffuse></material>
</visual>
</link>
</model>
<!-- A couple of interior obstacles to make mapping/localisation non-trivial -->
<model name="pillar_1">
<static>true</static>
<link name="link">
<pose>1.5 1.0 0.5 0 0 0</pose>
<collision name="c"><geometry><cylinder><radius>0.25</radius><length>1.0</length></cylinder></geometry></collision>
<visual name="v"><geometry><cylinder><radius>0.25</radius><length>1.0</length></cylinder></geometry>
<material><ambient>0.7 0.5 0.3 1</ambient><diffuse>0.7 0.5 0.3 1</diffuse></material></visual>
</link>
</model>
<model name="pillar_2">
<static>true</static>
<link name="link">
<pose>-1.8 -1.5 0.5 0 0 0</pose>
<collision name="c"><geometry><box><size>0.5 0.5 1.0</size></box></geometry></collision>
<visual name="v"><geometry><box><size>0.5 0.5 1.0</size></box></geometry>
<material><ambient>0.3 0.5 0.7 1</ambient><diffuse>0.3 0.5 0.7 1</diffuse></material></visual>
</link>
</model>
</world>
</sdf>
@@ -24,7 +24,7 @@ if(BUILD_TESTING)
endif() endif()
install( install(
DIRECTORY launch map param rviz scripts DIRECTORY config launch map param rviz scripts
DESTINATION share/${PROJECT_NAME} DESTINATION share/${PROJECT_NAME}
) )
@@ -0,0 +1,46 @@
# slam_toolbox online-async mapping config for the AGV Pro in simulation.
# Builds a map from /scan and publishes the map -> odom transform that Nav2
# needs. Frames match the robot: odom (from mecanum_drive_controller) and
# base_footprint (robot root). use_sim_time is supplied by the launch file.
slam_toolbox:
ros__parameters:
# Frames / topics
odom_frame: odom
map_frame: map
base_frame: base_footprint
scan_topic: /scan
mode: mapping
# Solver
solver_plugin: solver_plugins::CeresSolver
ceres_linear_solver: SPARSE_NORMAL_CHOLESKY
ceres_preconditioner: SCHUR_JACOBI
ceres_trust_strategy: LEVENBERG_MARQUARDT
ceres_dogleg_type: TRADITIONAL_DOGLEG
ceres_loss_function: None
# Mapping behaviour
map_update_interval: 1.0
resolution: 0.05
max_laser_range: 12.0
minimum_time_interval: 0.2
transform_timeout: 0.2
tf_buffer_duration: 30.0
stack_size_to_use: 40000000
enable_interactive_mode: true
# Scan matching
use_scan_matching: true
use_scan_barycenter: true
minimum_travel_distance: 0.3
minimum_travel_heading: 0.3
scan_buffer_size: 10
scan_buffer_maximum_scan_distance: 12.0
link_match_minimum_response_fine: 0.1
link_scan_maximum_distance: 1.5
loop_search_maximum_distance: 3.0
do_loop_closing: true
loop_match_minimum_chain_size: 10
loop_match_maximum_variance_coarse: 3.0
loop_match_minimum_response_coarse: 0.35
loop_match_minimum_response_fine: 0.45
@@ -0,0 +1,115 @@
"""
simulation.launch.py — Nav2 + SLAM in Gazebo for the AGV Pro.
Brings up the full autonomous-navigation stack in simulation:
1. Gazebo (agv_pro_gazebo.launch.py) in the walled `room.world`, with the
2D lidar publishing /scan and the mecanum_drive_controller publishing
odom -> base_footprint (TF) and /odom, consuming /cmd_vel.
2. slam_toolbox (online async) — builds a map from /scan and publishes
map -> odom.
3. Nav2 (navigation_launch.py) — planner / controller (MPPI, Omni motion
model for the holonomic base) / behaviours / bt_navigator, using
param/nav2_sim.yaml.
4. RViz with the navigation view.
Everything runs on the Gazebo clock (use_sim_time:=true).
Usage:
ros2 launch agv_pro_navigation2 simulation.launch.py
ros2 launch agv_pro_navigation2 simulation.launch.py headless:=true
ros2 launch agv_pro_navigation2 simulation.launch.py use_rviz:=false
"""
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import (
DeclareLaunchArgument,
IncludeLaunchDescription,
TimerAction,
)
from launch.conditions import IfCondition
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import Node
def generate_launch_description():
pkg_gazebo = get_package_share_directory('agv_pro_gazebo')
pkg_nav2 = get_package_share_directory('agv_pro_navigation2')
pkg_slam = get_package_share_directory('slam_toolbox')
pkg_nav2_bringup = get_package_share_directory('nav2_bringup')
use_rviz = LaunchConfiguration('use_rviz')
headless = LaunchConfiguration('headless')
world = LaunchConfiguration('world')
default_world = os.path.join(pkg_gazebo, 'worlds', 'room.world')
slam_params = os.path.join(pkg_nav2, 'config', 'slam_toolbox_sim.yaml')
nav2_params = os.path.join(pkg_nav2, 'param', 'nav2_sim.yaml')
rviz_config = os.path.join(pkg_nav2, 'rviz', 'agvpro_navigation2.rviz')
# 1. Gazebo + robot + lidar + controllers
gazebo = IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_gazebo, 'launch', 'agv_pro_gazebo.launch.py')
),
launch_arguments={
'use_sim_time': 'true',
'use_rviz': 'false',
'headless': headless,
'world': world,
}.items(),
)
# 2. SLAM (map -> odom). Delayed so /scan and odom TF are up first.
slam = IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_slam, 'launch', 'online_async_launch.py')
),
launch_arguments={
'use_sim_time': 'true',
'slam_params_file': slam_params,
}.items(),
)
# 3. Nav2 navigation stack (no localization; SLAM provides map -> odom).
nav2 = IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_nav2_bringup, 'launch', 'navigation_launch.py')
),
launch_arguments={
'use_sim_time': 'true',
'params_file': nav2_params,
}.items(),
)
# 4. RViz
rviz = Node(
package='rviz2',
executable='rviz2',
name='rviz2',
arguments=['-d', rviz_config],
parameters=[{'use_sim_time': True}],
condition=IfCondition(use_rviz),
output='screen',
)
# Give Gazebo time to spawn the robot and activate the controllers (which
# publish odom -> base_footprint) before SLAM and Nav2 start looking for TF.
delayed_bringup = TimerAction(period=8.0, actions=[slam, nav2, rviz])
return LaunchDescription([
DeclareLaunchArgument(
'use_rviz', default_value='true',
description='Launch RViz with the navigation view'),
DeclareLaunchArgument(
'headless', default_value='false',
description='Run gz-sim without the GUI (server only)'),
DeclareLaunchArgument(
'world', default_value=default_world,
description='Full path to the Gazebo world (SDF) to load'),
gazebo,
delayed_bringup,
])
@@ -12,6 +12,10 @@
<test_depend>ament_lint_auto</test_depend> <test_depend>ament_lint_auto</test_depend>
<test_depend>ament_lint_common</test_depend> <test_depend>ament_lint_common</test_depend>
<exec_depend>nav2_bringup</exec_depend> <exec_depend>nav2_bringup</exec_depend>
<exec_depend>slam_toolbox</exec_depend>
<exec_depend>agv_pro_gazebo</exec_depend>
<exec_depend>agv_pro_description</exec_depend>
<exec_depend>rviz2</exec_depend>
<export> <export>
<build_type>ament_cmake</build_type> <build_type>ament_cmake</build_type>
@@ -109,6 +109,9 @@ bt_navigator_rclcpp_node:
controller_server: controller_server:
ros__parameters: ros__parameters:
use_sim_time: False use_sim_time: False
# Publish /cmd_vel as geometry_msgs/TwistStamped to match the
# mecanum_drive_controller's ~/reference input (both sim and real robot).
enable_stamped_cmd_vel: true
controller_frequency: 20.0 controller_frequency: 20.0
min_x_velocity_threshold: 0.001 min_x_velocity_threshold: 0.001
min_y_velocity_threshold: 0.5 min_y_velocity_threshold: 0.5
@@ -0,0 +1,476 @@
amcl:
ros__parameters:
alpha1: 0.2
alpha2: 0.2
alpha3: 0.2
alpha4: 0.2
alpha5: 0.2
base_frame_id: "base_footprint"
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
bt_navigator:
ros__parameters:
global_frame: map
robot_base_frame: base_footprint
odom_topic: /odom
bt_loop_duration: 10
default_server_timeout: 20
wait_for_service_timeout: 1000
action_server_result_timeout: 900.0
navigators: ["navigate_to_pose", "navigate_through_poses"]
navigate_to_pose:
plugin: "nav2_bt_navigator::NavigateToPoseNavigator"
navigate_through_poses:
plugin: "nav2_bt_navigator::NavigateThroughPosesNavigator"
# '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 is used to add custom BT plugins to the executor (vector of strings).
# Built-in plugins are added automatically
# plugin_lib_names: []
error_code_names:
- compute_path_error_code
- follow_path_error_code
controller_server:
ros__parameters:
# Mecanum controller consumes geometry_msgs/TwistStamped on ~/reference.
enable_stamped_cmd_vel: true
controller_frequency: 20.0
costmap_update_timeout: 0.30
min_x_velocity_threshold: 0.001
min_y_velocity_threshold: 0.5
min_theta_velocity_threshold: 0.001
failure_tolerance: 0.3
progress_checker_plugins: ["progress_checker"]
goal_checker_plugins: ["general_goal_checker"] # "precise_goal_checker"
controller_plugins: ["FollowPath"]
use_realtime_priority: false
# 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
FollowPath:
plugin: "nav2_mppi_controller::MPPIController"
time_steps: 56
model_dt: 0.05
batch_size: 2000
ax_max: 3.0
ax_min: -3.0
ay_max: 3.0
ay_min: -3.0
az_max: 3.5
vx_std: 0.2
vy_std: 0.2
wz_std: 0.4
vx_max: 0.5
vx_min: -0.35
vy_max: 0.5
wz_max: 1.9
iteration_count: 1
prune_distance: 1.7
transform_tolerance: 0.1
temperature: 0.3
gamma: 0.015
motion_model: "Omni"
visualize: true
regenerate_noises: true
TrajectoryVisualizer:
trajectory_step: 5
time_step: 3
AckermannConstraints:
min_turning_r: 0.2
critics: [
"ConstraintCritic", "CostCritic", "GoalCritic",
"GoalAngleCritic", "PathAlignCritic", "PathFollowCritic",
"PathAngleCritic", "PreferForwardCritic"]
ConstraintCritic:
enabled: true
cost_power: 1
cost_weight: 4.0
GoalCritic:
enabled: true
cost_power: 1
cost_weight: 5.0
threshold_to_consider: 1.4
GoalAngleCritic:
enabled: true
cost_power: 1
cost_weight: 3.0
threshold_to_consider: 0.5
PreferForwardCritic:
enabled: true
cost_power: 1
cost_weight: 5.0
threshold_to_consider: 0.5
CostCritic:
enabled: true
cost_power: 1
cost_weight: 3.81
near_collision_cost: 253
critical_cost: 300.0
consider_footprint: false
collision_cost: 1000000.0
near_goal_distance: 1.0
trajectory_point_step: 2
PathAlignCritic:
enabled: true
cost_power: 1
cost_weight: 14.0
max_path_occupancy_ratio: 0.05
trajectory_point_step: 4
threshold_to_consider: 0.5
offset_from_furthest: 20
use_path_orientations: false
PathFollowCritic:
enabled: true
cost_power: 1
cost_weight: 5.0
offset_from_furthest: 5
threshold_to_consider: 1.4
PathAngleCritic:
enabled: true
cost_power: 1
cost_weight: 2.0
offset_from_furthest: 4
threshold_to_consider: 0.5
max_angle_to_furthest: 1.0
mode: 0
# TwirlingCritic:
# enabled: true
# twirling_cost_power: 1
# twirling_cost_weight: 10.0
local_costmap:
local_costmap:
ros__parameters:
update_frequency: 5.0
publish_frequency: 2.0
global_frame: odom
robot_base_frame: base_footprint
rolling_window: true
width: 3
height: 3
resolution: 0.05
robot_radius: 0.30
plugins: ["voxel_layer", "inflation_layer"]
inflation_layer:
plugin: "nav2_costmap_2d::InflationLayer"
cost_scaling_factor: 3.0
inflation_radius: 0.70
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
global_costmap:
global_costmap:
ros__parameters:
update_frequency: 1.0
publish_frequency: 1.0
global_frame: map
robot_base_frame: base_footprint
robot_radius: 0.30
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: 0.7
always_send_full_costmap: True
# The yaml_filename does not need to be specified since it going to be set by defaults in launch.
# If you'd rather set it in the yaml, remove the default "map" value in the tb3_simulation_launch.py
# file & provide full path to map below. If CLI map configuration or launch default is provided, that will be used.
# map_server:
# ros__parameters:
# yaml_filename: ""
map_saver:
ros__parameters:
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
planner_plugins: ["GridBased"]
costmap_update_timeout: 1.0
GridBased:
plugin: "nav2_navfn_planner::NavfnPlanner"
tolerance: 0.5
use_astar: false
allow_unknown: true
smoother_server:
ros__parameters:
smoother_plugins: ["simple_smoother"]
simple_smoother:
plugin: "nav2_smoother::SimpleSmoother"
tolerance: 1.0e-10
max_its: 1000
do_refinement: True
behavior_server:
ros__parameters:
enable_stamped_cmd_vel: true
local_costmap_topic: local_costmap/costmap_raw
global_costmap_topic: global_costmap/costmap_raw
local_footprint_topic: local_costmap/published_footprint
global_footprint_topic: global_costmap/published_footprint
cycle_frequency: 10.0
behavior_plugins: ["spin", "backup", "drive_on_heading", "assisted_teleop", "wait"]
spin:
plugin: "nav2_behaviors::Spin"
backup:
plugin: "nav2_behaviors::BackUp"
drive_on_heading:
plugin: "nav2_behaviors::DriveOnHeading"
wait:
plugin: "nav2_behaviors::Wait"
assisted_teleop:
plugin: "nav2_behaviors::AssistedTeleop"
local_frame: odom
global_frame: map
robot_base_frame: base_footprint
transform_tolerance: 0.1
simulate_ahead_time: 2.0
max_rotational_vel: 1.0
min_rotational_vel: 0.4
rotational_acc_lim: 3.2
waypoint_follower:
ros__parameters:
loop_rate: 20
stop_on_failure: false
action_server_result_timeout: 900.0
waypoint_task_executor_plugin: "wait_at_waypoint"
wait_at_waypoint:
plugin: "nav2_waypoint_follower::WaitAtWaypoint"
enabled: True
waypoint_pause_duration: 200
route_server:
ros__parameters:
# The graph_filepath does not need to be specified since it going to be set by defaults in launch.
# If you'd rather set it in the yaml, remove the default "graph" value in the launch file(s).
# file & provide full path to map below. If graph config or launch default is provided, it is used
# graph_filepath: $(find-pkg-share nav2_route)/graphs/aws_graph.geojson
boundary_radius_to_achieve_node: 1.0
radius_to_achieve_node: 2.0
smooth_corners: true
operations: ["AdjustSpeedLimit", "ReroutingService", "CollisionMonitor"]
ReroutingService:
plugin: "nav2_route::ReroutingService"
AdjustSpeedLimit:
plugin: "nav2_route::AdjustSpeedLimit"
CollisionMonitor:
plugin: "nav2_route::CollisionMonitor"
max_collision_dist: 3.0
edge_cost_functions: ["DistanceScorer", "CostmapScorer"]
DistanceScorer:
plugin: "nav2_route::DistanceScorer"
CostmapScorer:
plugin: "nav2_route::CostmapScorer"
velocity_smoother:
ros__parameters:
enable_stamped_cmd_vel: true
smoothing_frequency: 20.0
stamp_smoothed_velocity_with_smoothing_time: False
scale_velocities: False
feedback: "OPEN_LOOP"
max_velocity: [0.5, 0.5, 2.0]
min_velocity: [-0.5, -0.5, -2.0]
max_accel: [2.5, 2.5, 3.2]
max_decel: [-2.5, -2.5, -3.2]
odom_topic: "odom"
odom_duration: 0.1
deadband_velocity: [0.0, 0.0, 0.0]
velocity_timeout: 1.0
collision_monitor:
ros__parameters:
base_frame_id: "base_footprint"
odom_frame_id: "odom"
# Publish the final /cmd_vel as TwistStamped to match the mecanum controller.
enable_stamped_cmd_vel: true
cmd_vel_in_topic: "cmd_vel_smoothed"
cmd_vel_out_topic: "cmd_vel"
state_topic: "collision_monitor_state"
transform_tolerance: 0.2
source_timeout: 1.0
base_shift_correction: True
stop_pub_timeout: 2.0
# Polygons represent zone around the robot for "stop", "slowdown" and "limit" action types,
# and robot footprint for "approach" action type.
polygons: ["FootprintApproach"]
FootprintApproach:
type: "polygon"
action_type: "approach"
footprint_topic: "/local_costmap/published_footprint"
time_before_collision: 1.2
simulation_time_step: 0.1
min_points: 6
visualize: False
enabled: True
observation_sources: ["scan"]
scan:
type: "scan"
topic: "scan"
min_height: 0.15
max_height: 2.0
enabled: True
docking_server:
ros__parameters:
controller_frequency: 50.0
initial_perception_timeout: 5.0
wait_charge_timeout: 5.0
dock_approach_timeout: 30.0
undock_linear_tolerance: 0.05
undock_angular_tolerance: 0.1
max_retries: 3
base_frame: "base_link"
fixed_frame: "odom"
dock_backwards: false
dock_prestaging_tolerance: 0.5
# Types of docks
dock_plugins: ['simple_charging_dock']
simple_charging_dock:
plugin: 'opennav_docking::SimpleChargingDock'
docking_threshold: 0.05
staging_x_offset: -0.7
use_external_detection_pose: true
use_battery_status: false # true
use_stall_detection: false # true
external_detection_timeout: 1.0
external_detection_translation_x: -0.18
external_detection_translation_y: 0.0
external_detection_rotation_roll: -1.57
external_detection_rotation_pitch: -1.57
external_detection_rotation_yaw: 0.0
filter_coef: 0.1
# Dock instances
# The following example illustrates configuring dock instances.
# docks: ['home_dock'] # Input your docks here
# home_dock:
# type: 'simple_charging_dock'
# frame: map
# pose: [0.0, 0.0, 0.0]
controller:
k_phi: 3.0
k_delta: 2.0
v_linear_min: 0.15
v_linear_max: 0.15
use_collision_detection: true
costmap_topic: "local_costmap/costmap_raw"
footprint_topic: "local_costmap/published_footprint"
transform_tolerance: 0.1
projection_time: 5.0
simulation_step: 0.1
dock_collision_threshold: 0.3
loopback_simulator:
ros__parameters:
base_frame_id: "base_footprint"
odom_frame_id: "odom"
map_frame_id: "map"
scan_frame_id: "base_scan" # tb4_loopback_simulator.launch.py remaps to 'rplidar_link'
update_duration: 0.02
scan_range_min: 0.05
scan_range_max: 30.0
scan_angle_min: -3.1415
scan_angle_max: 3.1415
scan_angle_increment: 0.02617
scan_use_inf: true