Initial commit: ROS2 Gazebo GO2 simulation workspace

Made-with: Cursor
This commit is contained in:
lulijing
2026-04-10 13:01:08 +08:00
commit 239dda8530
732 changed files with 879960 additions and 0 deletions

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cmake_minimum_required(VERSION 3.8)
project(gazebo_sim)
if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
add_compile_options(-Wall -Wextra -Wpedantic)
endif()
# find dependencies
find_package(ament_cmake REQUIRED)
find_package(rclcpp REQUIRED)
find_package(urdf REQUIRED)
find_package(xacro REQUIRED)
find_package(std_msgs REQUIRED)
install(DIRECTORY
config
launch
world
rviz
models
DESTINATION share/${PROJECT_NAME}/
)
install(FILES dds/cyclonedds.xml DESTINATION share/${PROJECT_NAME}/dds)
ament_environment_hooks(
"${CMAKE_CURRENT_SOURCE_DIR}/environment/gazebo_models_path.dsv"
"${CMAKE_CURRENT_SOURCE_DIR}/environment/cyclonedds_uri.sh.in"
)
install(PROGRAMS
DESTINATION lib/${PROJECT_NAME}
)
install(
PROGRAMS
DESTINATION lib/${PROJECT_NAME}
)
ament_package()

3
src/gazebo_sim/README.md Normal file
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# go1_description
Quadruped robot
This package was build with ROS2 Galactic.

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### ekf config file ###
/**:
ekf_filter_node:
ros__parameters:
use_sim_time: true
# The frequency, in Hz, at which the filter will output a position estimate. Note that the filter will not begin
# computation until it receives at least one message from one of the inputs. It will then run continuously at the
# frequency specified here, regardless of whether it receives more measurements. Defaults to 30 if unspecified.
frequency: 30.0
# The period, in seconds, after which we consider a sensor to have timed out. In this event, we carry out a predict
# cycle on the EKF without correcting it. This parameter can be thought of as the minimum frequency with which the
# filter will generate new output. Defaults to 1 / frequency if not specified.
sensor_timeout: 0.1
# ekf_localization_node and ukf_localization_node both use a 3D omnidirectional motion model. If this parameter is
# set to true, no 3D information will be used in your state estimate. Use this if you are operating in a planar
# environment and want to ignore the effect of small variations in the ground plane that might otherwise be detected
# by, for example, an IMU. Defaults to false if unspecified.
two_d_mode: true
# Use this parameter to provide an offset to the transform generated by ekf_localization_node. This can be used for
# future dating the transform, which is required for interaction with some other packages. Defaults to 0.0 if
# unspecified.
transform_time_offset: 0.0
# Use this parameter to provide specify how long the tf listener should wait for a transform to become available.
# Defaults to 0.0 if unspecified.
transform_timeout: 0.0
# If you're having trouble, try setting this to true, and then echo the /diagnostics_agg topic to see if the node is
# unhappy with any settings or data.
print_diagnostics: true
# Debug settings. Not for the faint of heart. Outputs a ludicrous amount of information to the file specified by
# debug_out_file. I hope you like matrices! Please note that setting this to true will have strongly deleterious
# effects on the performance of the node. Defaults to false if unspecified.
debug: False
# Defaults to "robot_localization_debug.txt" if unspecified. Please specify the full path.
debug_out_file: ""
# Whether to broadcast the transformation over the /tf topic. Defaults to true if unspecified.
publish_tf: true
# Whether to publish the acceleration state. Defaults to false if unspecified.
publish_acceleration: false
# If the filter sees a jump back in time, the filter is reset (convenient for testing with rosbags!)
reset_on_time_jump: true
# REP-105 (http://www.ros.org/reps/rep-0105.html) specifies four principal coordinate frames: base_link, odom, map, and
# earth. base_link is the coordinate frame that is affixed to the robot. Both odom and map are world-fixed frames.
# The robot's position in the odom frame will drift over time, but is accurate in the short term and should be
# continuous. The odom frame is therefore the best frame for executing local motion plans. The map frame, like the odom
# frame, is a world-fixed coordinate frame, and while it contains the most globally accurate position estimate for your
# robot, it is subject to discrete jumps, e.g., due to the fusion of GPS data or a correction from a map-based
# localization node. The earth frame is used to relate multiple map frames by giving them a common reference frame.
# ekf_localization_node and ukf_localization_node are not concerned with the earth frame.
# Here is how to use the following settings:
# 1. Set the map_frame, odom_frame, and base_link frames to the appropriate frame names for your system.
# 1a. If your system does not have a map_frame, just remove it, and make sure "world_frame" is set to the value of
# odom_frame.
# 2. If you are fusing continuous position data such as wheel encoder odometry, visual odometry, or IMU data, set
# "world_frame" to your odom_frame value. This is the default behavior for robot_localization's state estimation nodes.
# 3. If you are fusing global absolute position data that is subject to discrete jumps (e.g., GPS or position updates
# from landmark observations) then:
# 3a. Set your "world_frame" to your map_frame value
# 3b. MAKE SURE something else is generating the odom->base_link transform. Note that this can even be another state
# estimation node from robot_localization! However, that instance should *not* fuse the global data.
map_frame: map # Defaults to "map" if unspecified
odom_frame: odom # Defaults to "odom" if unspecified
base_link_frame: base_link # Defaults to "base_link" if unspecified
world_frame: odom # Defaults to the value of odom_frame if unspecified
# The filter accepts an arbitrary number of inputs from each input message type (nav_msgs/Odometry,
# geometry_msgs/PoseWithCovarianceStamped, geometry_msgs/TwistWithCovarianceStamped,
# sensor_msgs/Imu). To add an input, simply append the next number in the sequence to its "base" name, e.g., odom0,
# odom1, twist0, twist1, imu0, imu1, imu2, etc. The value should be the topic name. These parameters obviously have no
# default values, and must be specified.
odom0: odom
# Each sensor reading updates some or all of the filter's state. These options give you greater control over which
# values from each measurement are fed to the filter. For example, if you have an odometry message as input, but only
# want to use its Z position value, then set the entire vector to false, except for the third entry. The order of the
# values is x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Note that not some message types
# do not provide some of the state variables estimated by the filter. For example, a TwistWithCovarianceStamped message
# has no pose information, so the first six values would be meaningless in that case. Each vector defaults to all false
# if unspecified, effectively making this parameter required for each sensor.
odom0_config: [true, true, true,
false, false, false,
true, true, true,
false, false, true,
false, false, false]
# [x_pos , y_pos , z_pos,
# roll , pitch , yaw,
# x_vel , y_vel , z_vel,
# roll_vel, pitch_vel, yaw_vel,
# x_accel , y_accel , z_accel]
# If you have high-frequency data or are running with a low frequency parameter value, then you may want to increase
# the size of the subscription queue so that more measurements are fused.
odom0_queue_size: 2
# [ADVANCED] Large messages in ROS can exhibit strange behavior when they arrive at a high frequency. This is a result
# of Nagle's algorithm. This option tells the ROS subscriber to use the tcpNoDelay option, which disables Nagle's
# algorithm.
odom0_nodelay: false
# [ADVANCED] When measuring one pose variable with two sensors, a situation can arise in which both sensors under-
# report their covariances. This can lead to the filter rapidly jumping back and forth between each measurement as they
# arrive. In these cases, it often makes sense to (a) correct the measurement covariances, or (b) if velocity is also
# measured by one of the sensors, let one sensor measure pose, and the other velocity. However, doing (a) or (b) isn't
# always feasible, and so we expose the differential parameter. When differential mode is enabled, all absolute pose
# data is converted to velocity data by differentiating the absolute pose measurements. These velocities are then
# integrated as usual. NOTE: this only applies to sensors that provide pose measurements; setting differential to true
# for twist measurements has no effect.
odom0_differential: false
# [ADVANCED] When the node starts, if this parameter is true, then the first measurement is treated as a "zero point"
# for all future measurements. While you can achieve the same effect with the differential paremeter, the key
# difference is that the relative parameter doesn't cause the measurement to be converted to a velocity before
# integrating it. If you simply want your measurements to start at 0 for a given sensor, set this to true.
odom0_relative: false
# [ADVANCED] If your data is subject to outliers, use these threshold settings, expressed as Mahalanobis distances, to
# control how far away from the current vehicle state a sensor measurement is permitted to be. Each defaults to
# numeric_limits<double>::max() if unspecified. It is strongly recommended that these parameters be removed if not
# required. Data is specified at the level of pose and twist variables, rather than for each variable in isolation.
# For messages that have both pose and twist data, the parameter specifies to which part of the message we are applying
# the thresholds.
odom0_pose_rejection_threshold: 5.0
odom0_twist_rejection_threshold: 1.0
imu0: imu_plugin/out
imu0_config: [false, false, false,
true, true, true,
false, false, false,
true, true, true,
true, true, true]
# [x_pos , y_pos , z_pos,
# roll , pitch , yaw,
# x_vel , y_vel , z_vel,
# roll_vel, pitch_vel, yaw_vel,
# x_accel , y_accel , z_accel]
imu0_nodelay: false
imu0_differential: false
imu0_relative: true
imu0_queue_size: 7
imu0_pose_rejection_threshold: 0.8 # Note the difference in parameter names
imu0_twist_rejection_threshold: 0.8 #
imu0_linear_acceleration_rejection_threshold: 0.8 #
# [ADVANCED] Some IMUs automatically remove acceleration due to gravity, and others don't. If yours doesn't, please set
# this to true, and *make sure* your data conforms to REP-103, specifically, that the data is in ENU frame.
imu0_remove_gravitational_acceleration: true
# [ADVANCED] The EKF and UKF models follow a standard predict/correct cycle. During prediction, if there is no
# acceleration reference, the velocity at time t+1 is simply predicted to be the same as the velocity at time t. During
# correction, this predicted value is fused with the measured value to produce the new velocity estimate. This can be
# problematic, as the final velocity will effectively be a weighted average of the old velocity and the new one. When
# this velocity is the integrated into a new pose, the result can be sluggish covergence. This effect is especially
# noticeable with LIDAR data during rotations. To get around it, users can try inflating the process_noise_covariance
# for the velocity variable in question, or decrease the variance of the variable in question in the measurement
# itself. In addition, users can also take advantage of the control command being issued to the robot at the time we
# make the prediction. If control is used, it will get converted into an acceleration term, which will be used during
# predicition. Note that if an acceleration measurement for the variable in question is available from one of the
# inputs, the control term will be ignored.
# Whether or not we use the control input during predicition. Defaults to false.
use_control: false
# Whether the input (assumed to be cmd_vel) is a geometry_msgs/Twist or geometry_msgs/TwistStamped message. Defaults to
# false.
stamped_control: false
# The last issued control command will be used in prediction for this period. Defaults to 0.2.
control_timeout: 0.2
# Which velocities are being controlled. Order is vx, vy, vz, vroll, vpitch, vyaw.
control_config: [true, true, false, false, false, true]
# Places limits on how large the acceleration term will be. Should match your robot's kinematics.
acceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 3.4]
# Acceleration and deceleration limits are not always the same for robots.
deceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 4.5]
# If your robot cannot instantaneously reach its acceleration limit, the permitted change can be controlled with these
# gains
acceleration_gains: [0.8, 0.0, 0.0, 0.0, 0.0, 0.9]
# If your robot cannot instantaneously reach its deceleration limit, the permitted change can be controlled with these
# gains
deceleration_gains: [1.0, 0.0, 0.0, 0.0, 0.0, 1.0]
# [ADVANCED] The process noise covariance matrix can be difficult to tune, and can vary for each application, so it is
# exposed as a configuration parameter. This matrix represents the noise we add to the total error after each
# prediction step. The better the omnidirectional motion model matches your system, the smaller these values can be.
# However, if users find that a given variable is slow to converge, one approach is to increase the
# process_noise_covariance diagonal value for the variable in question, which will cause the filter's predicted error
# to be larger, which will cause the filter to trust the incoming measurement more during correction. The values are
# ordered as x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Defaults to the matrix below if
# unspecified.
process_noise_covariance: [0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.02, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.015]
# [ADVANCED] This represents the initial value for the state estimate error covariance matrix. Setting a diagonal
# value (variance) to a large value will result in rapid convergence for initial measurements of the variable in
# question. Users should take care not to use large values for variables that will not be measured directly. The values
# are ordered as x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Defaults to the matrix below
#if unspecified.
initial_estimate_covariance: [1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1e-9]

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controller_manager:
ros__parameters:
use_sim_time: true

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- ros_topic_name: "clock"
gz_topic_name: "clock"
ros_type_name: "rosgraph_msgs/msg/Clock"
gz_type_name: "gz.msgs.Clock"
direction: GZ_TO_ROS

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/**:
controller_manager:
ros__parameters:
update_rate: 100 #Hz
joint_state_broadcaster:
type: joint_state_broadcaster/JointStateBroadcaster
joint_group_controller:
type: position_controllers/JointGroupPositionController
joint_group_controller:
ros__parameters:
joints:
- FR_hip_joint
- FR_thigh_joint
- FR_calf_joint
- FL_hip_joint
- FL_thigh_joint
- FL_calf_joint
- RR_hip_joint
- RR_thigh_joint
- RR_calf_joint
- RL_hip_joint
- RL_thigh_joint
- RL_calf_joint

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robots:
- name: robot1
x_pose: '0.0'
y_pose: '0.0'
z_pose: '0.8'
# - name: robot2
# x_pose: '-2.0'
# y_pose: '0.0'
# z_pose: '0.8'
# - name: robot3
# x_pose: '0.0'
# y_pose: '-2.0'
# z_pose: '0.8'
# - name: robot4
# x_pose: '-2.0'
# y_pose: '-2.0'
# z_pose: '0.8'
# add more robots if you need, but unable multi robots in cyclonedds config file

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<CycloneDDS>
<Domain>
<General>
<Interfaces>
<NetworkInterface name="lo" multicast="true" />
</Interfaces>
<DontRoute>true</DontRoute>
</General>
<Discovery>
<ParticipantIndex>auto</ParticipantIndex>
<MaxAutoParticipantIndex>100</MaxAutoParticipantIndex>
</Discovery>
</Domain>
</CycloneDDS>

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# CycloneDDS: use absolute path (file://~/... does not expand ~)
export CYCLONEDDS_URI="file://@CMAKE_INSTALL_PREFIX@/share/gazebo_sim/dds/cyclonedds.xml"

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prepend-non-duplicate;GZ_SIM_RESOURCE_PATH;share/gazebo_sim/models
prepend-non-duplicate;IGN_GAZEBO_RESOURCE_PATH;share/gazebo_sim/models

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import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import (
IncludeLaunchDescription,
DeclareLaunchArgument,
ExecuteProcess,
GroupAction,
RegisterEventHandler
)
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration
from launch_ros.descriptions import ComposableNode
from launch.conditions import IfCondition
from launch_ros.actions import Node, SetRemap, ComposableNodeContainer
from launch.event_handlers import OnProcessExit
import xacro, yaml
def generate_launch_description():
ld = LaunchDescription()
# ---------- 基础配置 ----------
package_name = 'gazebo_sim'
pkg_path = get_package_share_directory(package_name)
robots_file_path = os.path.join(pkg_path, 'config', 'robots.yaml')
# 多机器人配置
with open(robots_file_path, 'r') as file:
yaml_data = yaml.safe_load(file)
robots = yaml_data['robots']
# ---------- 声明启动参数 ----------
use_sim_time = LaunchConfiguration('use_sim_time', default='true')
declare_use_sim_time = DeclareLaunchArgument(
name='use_sim_time',
default_value='true',
description='仿真时间是否使用'
)
enable_rviz = LaunchConfiguration('enable_rviz', default='true')
declare_enable_rviz = DeclareLaunchArgument(
name='enable_rviz', default_value=enable_rviz, description='Enable rviz launch'
)
ld.add_action(declare_enable_rviz)
ld.add_action(declare_use_sim_time)
# ---------- 多机器人全局话题重映射 ----------
remappings=[
("/tf", "tf"),
("/tf_static", "tf_static"),
("/scan", "scan"),
("/odom", "odometry/filtered")
]
# ---------- Gazebo-ROS时间同步配置 ----------
bridge_params = os.path.join(pkg_path,'config','gz_bridge.yaml')
ros_gz_bridge_clock = Node(
package="ros_gz_bridge",
executable="parameter_bridge",
arguments=[
'--ros-args',
'-p',
f'config_file:={bridge_params}',
]
)
ld.add_action(ros_gz_bridge_clock)
# ---------- 多机器人循环启动 ----------
last_action = None
for i, robot in enumerate(robots):
namespace = robot['name']
robot_name = robot['name']
xacro_file = os.path.join(os.path.join(get_package_share_directory('go2_description')), 'xacro', 'robot.xacro') ## CHANGE ME!!!!
robot_desc = xacro.process_file(xacro_file, mappings={'robot_name': robot_name}).toxml()
params_robot_state_publisher = {'robot_description': robot_desc, 'use_sim_time': use_sim_time}
node_robot_state_publisher = Node(
package='robot_state_publisher',
executable='robot_state_publisher',
output='screen',
namespace=namespace,
parameters=[params_robot_state_publisher],
remappings=remappings
)
spawn_entity = Node(
package='ros_gz_sim',
executable='create',
namespace=namespace,
arguments=[
'-topic', f'/{namespace}/robot_description',
'-name', f'{namespace}_my_bot',
'-allow_renaming', 'true',
'-x', robot['x_pose'],
'-y', robot['y_pose'],
'-z', robot['z_pose'],
# '-Y', robot['Y_pose']
],
output='screen'
)
ros_gz_bridge = Node(
package='ros_gz_bridge',
executable='parameter_bridge',
namespace=namespace,
name='ros_gz_bridge',
output='screen',
arguments=[
f'/{namespace}/imu_plugin/out@sensor_msgs/msg/Imu@gz.msgs.IMU',
f'/{namespace}/scan@sensor_msgs/msg/LaserScan@gz.msgs.LaserScan',
f'/{namespace}/scan/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked',
f'/{namespace}/tf@tf2_msgs/msg/TFMessage@gz.msgs.Pose_V',
f'/{namespace}/joint_states@sensor_msgs/msg/JointState@gz.msgs.Model',
f'/{namespace}/color/camera_info@sensor_msgs/msg/CameraInfo@gz.msgs.CameraInfo',
f'/{namespace}/color/image_raw@sensor_msgs/msg/Image@gz.msgs.Image',
# f'/{namespace}/clock@rosgraph_msgs/msg/Clock@gz.msgs.Clock'
]
)
start_gazebo_ros_image_bridge_cmd = Node(
package='ros_gz_image',
executable='image_bridge',
namespace=namespace,
arguments=['color/image_raw',
],
output='screen',
)
joint_state_broadcaster = Node(
package='controller_manager',
executable='spawner',
namespace=namespace,
name='joint_state_broadcaster',
arguments=['joint_state_broadcaster'],
output='screen',
remappings=remappings
)
joint_group_controller = Node(
package='controller_manager',
executable='spawner',
namespace=namespace,
name='joint_group_controller',
arguments=['joint_group_controller'],
output='screen',
remappings=remappings
)
controller = Node(
package='quadropted_controller',
executable='robot_controller_gazebo.py',
name='quadruped_controller',
namespace=namespace,
output='screen',
remappings=remappings
)
odom = Node(
package='quadropted_controller',
executable='QuadrupedOdometryNode.py',
name='odom',
namespace=namespace,
output='screen',
parameters=[{
"verbose": False,
'publish_rate': 50,
'open_loop': False,
'has_imu_heading': True,
'is_gazebo': True,
'imu_topic': f'/{namespace}/imu',
'base_frame_id': "base_link",
'odom_frame_id': "odom",
'clock_topic': f'/clock',
'enable_odom_tf': True,
}],
remappings=remappings
)
rviz_launch_file = os.path.join(pkg_path, 'launch', 'rviz_launch.py')
rviz_config_file = os.path.join(pkg_path, 'rviz', 'go2_self.rviz')
rviz = IncludeLaunchDescription(
PythonLaunchDescriptionSource(rviz_launch_file),
launch_arguments={
"namespace": namespace,
"use_namespace": 'true',
"rviz_config": rviz_config_file,
}.items(),
condition=IfCondition(enable_rviz)
)
cmd_vel_pub = Node(
package='quadropted_controller',
executable='cmd_vel_pub.py',
namespace=namespace,
name='cmd_vel_pub',
output='screen',
remappings=remappings
)
fake_bms = ExecuteProcess(
cmd=[
'ros2', 'topic', 'pub', f'/{namespace}/battery_state', 'sensor_msgs/msg/BatteryState',
"{header: {stamp: {sec: 0, nanosec: 0}, frame_id: ''}, voltage: 24.0, percentage: 0.8, capacity: 10.0}",
'-r', '1'
],
output='log'
)
robot_localization_file_path = os.path.join(pkg_path, 'config', 'ekf.yaml')
# Start robot localization using an Extended Kalman filter
start_robot_localization_cmd = Node(
package='robot_localization',
executable='ekf_node',
name='ekf_filter_node',
namespace=namespace,
output='screen',
parameters=[robot_localization_file_path,
{'use_sim_time': use_sim_time}],
remappings=remappings)
robot_control = GroupAction([
SetRemap(src="/tf", dst="tf"),
SetRemap(src="/tf_static", dst="tf_static"),
joint_state_broadcaster,
joint_group_controller,
controller,
cmd_vel_pub,
odom,
start_robot_localization_cmd,
fake_bms,
])
# 当前机器人动作组
robot_group = GroupAction([
node_robot_state_publisher,
spawn_entity,
ros_gz_bridge,
start_gazebo_ros_image_bridge_cmd,
robot_control,
rviz,
])
if last_action is None:
ld.add_action(robot_group)
else:
spawn_robot_event = RegisterEventHandler(
event_handler=OnProcessExit(
target_action=last_action,
on_exit=[robot_group]
)
)
ld.add_action(spawn_robot_event)
last_action = joint_group_controller
return ld

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import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import (
IncludeLaunchDescription,
DeclareLaunchArgument,
ExecuteProcess,
GroupAction,
RegisterEventHandler
)
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration
from launch_ros.descriptions import ComposableNode
from launch.conditions import IfCondition
from launch_ros.actions import Node, SetRemap, ComposableNodeContainer
from launch.event_handlers import OnProcessExit
import xacro, yaml
def generate_launch_description():
ld = LaunchDescription()
# ---------- 基础配置 ----------
package_name = 'gazebo_sim'
pkg_path = get_package_share_directory(package_name)
robots_file_path = os.path.join(pkg_path, 'config', 'robots.yaml')
# 多机器人配置
with open(robots_file_path, 'r') as file:
yaml_data = yaml.safe_load(file)
robots = yaml_data['robots']
# ---------- 声明启动参数 ----------
use_sim_time = LaunchConfiguration('use_sim_time', default='true')
declare_use_sim_time = DeclareLaunchArgument(
name='use_sim_time',
default_value='true',
description='仿真时间是否使用'
)
enable_rviz = LaunchConfiguration('enable_rviz', default='true')
declare_enable_rviz = DeclareLaunchArgument(
name='enable_rviz', default_value=enable_rviz, description='Enable rviz launch'
)
ld.add_action(declare_enable_rviz)
ld.add_action(declare_use_sim_time)
# ---------- 多机器人全局话题重映射 ----------
remappings=[
("/tf", "tf"),
("/tf_static", "tf_static"),
("/scan", "scan"),
("/odom", "odometry/filtered")
]
# ---------- Gazebo-ROS时间同步配置 ----------
bridge_params = os.path.join(pkg_path,'config','gz_bridge.yaml')
ros_gz_bridge_clock = Node(
package="ros_gz_bridge",
executable="parameter_bridge",
arguments=[
'--ros-args',
'-p',
f'config_file:={bridge_params}',
]
)
ld.add_action(ros_gz_bridge_clock)
# ---------- 多机器人循环启动 ----------
last_action = None
for i, robot in enumerate(robots):
namespace = robot['name']
robot_name = robot['name']
xacro_file = os.path.join(os.path.join(get_package_share_directory('go2_description')), 'xacro', 'robot_VLP_D435i.xacro') ## CHANGE ME!!!!
robot_desc = xacro.process_file(xacro_file, mappings={'robot_name': robot_name}).toxml()
params_robot_state_publisher = {'robot_description': robot_desc, 'use_sim_time': use_sim_time}
node_robot_state_publisher = Node(
package='robot_state_publisher',
executable='robot_state_publisher',
output='screen',
namespace=namespace,
parameters=[params_robot_state_publisher],
remappings=remappings
)
spawn_entity = Node(
package='ros_gz_sim',
executable='create',
namespace=namespace,
arguments=[
'-topic', f'/{namespace}/robot_description',
'-name', f'{namespace}_my_bot',
'-allow_renaming', 'true',
'-x', robot['x_pose'],
'-y', robot['y_pose'],
'-z', robot['z_pose'],
# '-Y', robot['Y_pose']
],
output='screen'
)
ros_gz_bridge = Node(
package='ros_gz_bridge',
executable='parameter_bridge',
namespace=namespace,
name='ros_gz_bridge',
output='screen',
arguments=[
f'/{namespace}/imu_plugin/out@sensor_msgs/msg/Imu@gz.msgs.IMU',
f'/{namespace}/scan@sensor_msgs/msg/LaserScan@gz.msgs.LaserScan',
f'/{namespace}/scan/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked',
f'/{namespace}/velodyne@sensor_msgs/msg/LaserScan@gz.msgs.LaserScan',
f'/{namespace}/velodyne/points@sensor_msgs/msg/PointCloud2@gz.msgs.PointCloudPacked',
f'/{namespace}/velodyne_imu@sensor_msgs/msg/Imu@gz.msgs.IMU',
f'/{namespace}/tf@tf2_msgs/msg/TFMessage@gz.msgs.Pose_V',
f'/{namespace}/joint_states@sensor_msgs/msg/JointState@gz.msgs.Model',
f'/{namespace}/color/camera_info@sensor_msgs/msg/CameraInfo@gz.msgs.CameraInfo',
f'/{namespace}/color/image_raw@sensor_msgs/msg/Image@gz.msgs.Image',
f'/{namespace}/d435i_imu@sensor_msgs/msg/Imu@gz.msgs.IMU',
# f'/{namespace}/clock@rosgraph_msgs/msg/Clock@gz.msgs.Clock'
]
)
start_gazebo_ros_image_bridge_cmd = Node(
package='ros_gz_image',
executable='image_bridge',
namespace=namespace,
arguments=['color/image_raw',
],
output='screen',
)
gz_image_bridge_node = Node(
package="ros_gz_image",
executable="image_bridge",
namespace=namespace,
arguments=[
f'/{namespace}/rgbd_d435/depth_image',
f'/{namespace}/rgbd_d435/image',
],
output="screen",
parameters=[
{'use_sim_time': True,
'camera.image.compressed.jpeg_quality': 75},
],
)
joint_state_broadcaster = Node(
package='controller_manager',
executable='spawner',
namespace=namespace,
name='joint_state_broadcaster',
arguments=['joint_state_broadcaster'],
output='screen',
remappings=remappings
)
joint_group_controller = Node(
package='controller_manager',
executable='spawner',
namespace=namespace,
name='joint_group_controller',
arguments=['joint_group_controller'],
output='screen',
remappings=remappings
)
controller = Node(
package='quadropted_controller',
executable='robot_controller_gazebo.py',
name='quadruped_controller',
namespace=namespace,
output='screen',
remappings=remappings
)
odom = Node(
package='quadropted_controller',
executable='QuadrupedOdometryNode.py',
name='odom',
namespace=namespace,
output='screen',
parameters=[{
"verbose": False,
'publish_rate': 50,
'open_loop': False,
'has_imu_heading': True,
'is_gazebo': True,
'imu_topic': f'/{namespace}/imu',
'base_frame_id': "base_link",
'odom_frame_id': "odom",
'clock_topic': f'/clock',
'enable_odom_tf': True,
}],
remappings=remappings
)
rviz_launch_file = os.path.join(pkg_path, 'launch', 'rviz_launch.py')
rviz_config_file = os.path.join(pkg_path, 'rviz', 'go2_sensors.rviz')
rviz = IncludeLaunchDescription(
PythonLaunchDescriptionSource(rviz_launch_file),
launch_arguments={
"namespace": namespace,
"use_namespace": 'true',
"rviz_config": rviz_config_file,
}.items(),
condition=IfCondition(enable_rviz)
)
cmd_vel_pub = Node(
package='quadropted_controller',
executable='cmd_vel_pub.py',
namespace=namespace,
name='cmd_vel_pub',
output='screen',
remappings=remappings
)
fake_bms = ExecuteProcess(
cmd=[
'ros2', 'topic', 'pub', f'/{namespace}/battery_state', 'sensor_msgs/msg/BatteryState',
"{header: {stamp: {sec: 0, nanosec: 0}, frame_id: ''}, voltage: 24.0, percentage: 0.8, capacity: 10.0}",
'-r', '1'
],
output='log'
)
robot_localization_file_path = os.path.join(pkg_path, 'config', 'ekf.yaml')
# Start robot localization using an Extended Kalman filter
start_robot_localization_cmd = Node(
package='robot_localization',
executable='ekf_node',
name='ekf_filter_node',
namespace=namespace,
output='screen',
parameters=[robot_localization_file_path,
{'use_sim_time': use_sim_time}],
remappings=remappings)
robot_control = GroupAction([
SetRemap(src="/tf", dst="tf"),
SetRemap(src="/tf_static", dst="tf_static"),
joint_state_broadcaster,
joint_group_controller,
controller,
cmd_vel_pub,
odom,
start_robot_localization_cmd,
fake_bms,
])
# 当前机器人动作组
robot_group = GroupAction([
node_robot_state_publisher,
spawn_entity,
ros_gz_bridge,
start_gazebo_ros_image_bridge_cmd,
robot_control,
gz_image_bridge_node,
rviz,
])
if last_action is None:
ld.add_action(robot_group)
else:
spawn_robot_event = RegisterEventHandler(
event_handler=OnProcessExit(
target_action=last_action,
on_exit=[robot_group]
)
)
ld.add_action(spawn_robot_event)
last_action = joint_group_controller
return ld

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import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription, LaunchContext
from launch.actions import (
IncludeLaunchDescription,
DeclareLaunchArgument,
ExecuteProcess,
RegisterEventHandler,
OpaqueFunction
)
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration
from launch.event_handlers import OnProcessExit
from launch_ros.actions import SetParameter
def create_gazebo_action(context: LaunchContext, package_name: str):
world_name = LaunchConfiguration('world').perform(context)
pkg_path = get_package_share_directory(package_name)
world_file = os.path.join(pkg_path, 'world', world_name)
gazebo_action = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(
get_package_share_directory('ros_gz_sim'), 'launch', 'gz_sim.launch.py')),
launch_arguments={
'gz_args': ['-r -v4 ', world_file],
'on_exit_shutdown': 'true'
}.items()
)
return [gazebo_action]
def choose_launch_file(context, *args, **kwargs):
use_sensors = LaunchConfiguration('sensors').perform(context)
package_name = 'gazebo_sim'
pkg_path = get_package_share_directory(package_name)
if use_sensors.lower() == 'true':
launch_file = 'gazebo_go2_sensors.launch.py'
else:
launch_file = 'gazebo_go2_self.launch.py'
return [
IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_path, 'launch', launch_file)
)
)
]
def generate_launch_description():
ld = LaunchDescription()
package_name = 'gazebo_sim'
use_sim_time = LaunchConfiguration('use_sim_time', default='true')
ld.add_action(DeclareLaunchArgument(
'use_sim_time',
default_value='true',
description='是否使用仿真时间'
))
ld.add_action(SetParameter(name='use_sim_time', value=use_sim_time))
ld.add_action(DeclareLaunchArgument(
'sensors',
default_value='false',
description='是否启动传感器版launch文件默认启动无外置传感器版'
))
ld.add_action(DeclareLaunchArgument(
'world',
default_value='rmuc_2025_world.sdf',
description='指定要加载的Gazebo世界文件需放在gazebo_sim/world目录下'
))
gazebo_action = OpaqueFunction(
function=create_gazebo_action,
args=[package_name]
)
ld.add_action(gazebo_action)
pause = ExecuteProcess(
cmd=['sleep', '6'],
output='screen'
)
ld.add_action(pause)
go2_sensors_launch = OpaqueFunction(function=choose_launch_file)
launch_after_pause = RegisterEventHandler(
event_handler=OnProcessExit(
target_action=pause,
on_exit=[go2_sensors_launch]
)
)
ld.add_action(launch_after_pause)
return ld

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import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import IncludeLaunchDescription, DeclareLaunchArgument
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import Node
import xacro
def generate_launch_description():
package_name='gazebo_sim'
namespace = '/robot1'
name = 'robot1'
# Process the URDF file
pkg_path = os.path.join(get_package_share_directory(package_name))
xacro_file = os.path.join(pkg_path,'xacro','robot.xacro')
remappings = [
("/tf", "tf"),
("/tf_static", "tf_static"),
("/scan", "scan"),
("/odom", "odom")
]
use_sim_time = LaunchConfiguration('use_sim_time', default='true')
declare_use_sim_time = DeclareLaunchArgument(
name='use_sim_time', default_value=use_sim_time, description='仿真时间'
)
world = os.path.join(pkg_path, 'world', 'empty.world')
# Include the Gazebo launch file, provided by the ros_gz_sim package
gazebo = IncludeLaunchDescription(
PythonLaunchDescriptionSource([os.path.join(
get_package_share_directory('ros_gz_sim'), 'launch', 'gz_sim.launch.py')]),
launch_arguments={'gz_args': ['-r -v4 ', world], 'on_exit_shutdown': 'true'}.items()
)
# Run the spawner node from the ros_gz_sim package. The entity name doesn't really matter if you only have a single robot.
spawn_entity = Node(package='ros_gz_sim', executable='create', namespace=namespace,
arguments=['-topic', f'{namespace}/robot_description',
'-name', f'{namespace}/my_bot',
'-z', '0.4'],
output='screen')
robot_desc = xacro.process_file(
xacro_file,
mappings={'robot_name': name}
).toxml()
params = {'robot_description': robot_desc, 'use_sim_time': use_sim_time}
node_robot_state_publisher = Node(
package='robot_state_publisher',
executable='robot_state_publisher',
output='screen',
namespace=namespace,
parameters=[params],
remappings=remappings
)
bridge_params = os.path.join(get_package_share_directory(package_name),'config','gz_bridge.yaml')
ros_gz_bridge = Node(
package="ros_gz_bridge",
executable="parameter_bridge",
namespace=namespace,
arguments=[
f"{namespace}/imu_plugin/out@sensor_msgs/msg/Imu@gz.msgs.IMU",
f"{namespace}/scan@sensor_msgs/msg/LaserScan@gz.msgs.LaserScan",
f"{namespace}/tf@tf2_msgs/msg/TFMessage@gz.msgs.Pose_V",
f"{namespace}/joint_states@sensor_msgs/msg/JointState@gz.msgs.Model"
]
)
ros_gz_bridge_clock = Node(
package="ros_gz_bridge",
executable="parameter_bridge",
arguments=[
'--ros-args',
'-p',
f'config_file:={bridge_params}',
]
)
joint_state_broadcaster = Node(
package="controller_manager",
executable="spawner",
namespace=namespace,
arguments=["joint_state_broadcaster"],
remappings=remappings
)
joint_group_controller = Node(
package="controller_manager",
executable="spawner",
namespace=namespace,
arguments=["joint_group_controller"],
output="screen",
remappings=remappings
)
controller = Node(
package='quadropted_controller',
executable='robot_controller_gazebo.py',
name='quadruped_controller',
namespace=namespace,
output='screen',
remappings=remappings
)
cmd_vel_pub = Node(
package='quadropted_controller',
executable='cmd_vel_pub.py',
name='cmd_vel_pub',
namespace=namespace,
output='screen',
)
odom =Node(
package='quadropted_controller',
executable='QuadrupedOdometryNode.py',
name='odom',
namespace=namespace,
output='screen',
parameters=[{
"verbose": False,
'publish_rate': 50,
'open_loop': False,
'has_imu_heading': True,
'is_gazebo': True,
'imu_topic': f"/{namespace}/imu",
'base_frame_id': "base",
'odom_frame_id': "odom",
'clock_topic': '/clock',
'enable_odom_tf': True,
}],
remappings=remappings
)
params_file = os.path.join(get_package_share_directory(package_name), 'config', 'nav2_params.yaml')
map_dir = os.path.join(get_package_share_directory(package_name), 'maps', 'warehouse_map.yaml')
bringup_cmd = IncludeLaunchDescription(
PythonLaunchDescriptionSource(
os.path.join(pkg_path, 'launch', 'nav2', 'bringup_launch.py')),
launch_arguments={
'map': map_dir,
'use_namespace': 'True',
'namespace': namespace,
'params_file': params_file,
'autostart': 'true',
'use_sim_time': 'True',
'log_level': 'warn',
'map_server': 'True'
}.items()
)
rviz_config_file = os.path.join(pkg_path, 'config', 'multi_nav2_default_view.rviz')
rviz = IncludeLaunchDescription(
PythonLaunchDescriptionSource(os.path.join(pkg_path, 'launch', "rviz_launch.py")),
launch_arguments={
"namespace": namespace,
"use_namespace": 'true',
"rviz_config": rviz_config_file,
}.items()
)
# Launch them all!
return LaunchDescription([
declare_use_sim_time,
node_robot_state_publisher,
gazebo,
spawn_entity,
ros_gz_bridge,
ros_gz_bridge_clock,
joint_state_broadcaster,
joint_group_controller,
controller,
cmd_vel_pub,
odom,
rviz,
# bringup_cmd
])

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# Copyright (c) 2018 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument, EmitEvent, RegisterEventHandler
from launch.conditions import IfCondition, UnlessCondition
from launch.event_handlers import OnProcessExit
from launch.events import Shutdown
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import Node
from nav2_common.launch import ReplaceString
def generate_launch_description():
# Get the launch directory
bringup_dir = get_package_share_directory('gazebo_sim')
# Create the launch configuration variables
namespace = LaunchConfiguration('namespace')
use_namespace = LaunchConfiguration('use_namespace')
rviz_config_file = LaunchConfiguration('rviz_config')
# Declare the launch arguments
declare_namespace_cmd = DeclareLaunchArgument(
'namespace',
default_value='navigation',
description=('Top-level namespace. The value will be used to replace the '
'<robot_namespace> keyword on the rviz config file.'))
declare_use_namespace_cmd = DeclareLaunchArgument(
'use_namespace',
default_value='false',
description='Whether to apply a namespace to the navigation stack')
declare_rviz_config_file_cmd = DeclareLaunchArgument(
'rviz_config',
default_value=os.path.join(bringup_dir, 'rviz', 'multi_nav2_default_view.rviz'),
description='Full path to the RVIZ config file to use')
# Launch rviz
start_rviz_cmd = Node(
condition=UnlessCondition(use_namespace),
package='rviz2',
executable='rviz2',
arguments=['-d', rviz_config_file],
output='screen')
namespaced_rviz_config_file = ReplaceString(
source_file=rviz_config_file,
replacements={'<robot_namespace>': ('/', namespace)})
start_namespaced_rviz_cmd = Node(
condition=IfCondition(use_namespace),
package='rviz2',
executable='rviz2',
namespace=namespace,
arguments=['-d', namespaced_rviz_config_file],
output='screen',
remappings=[('/tf', 'tf'),
('/tf_static', 'tf_static'),
('/goal_pose', 'goal_pose'),
("/odom", "odometry/filtered"),
('/clicked_point', 'clicked_point'),
('/initialpose', 'initialpose')])
exit_event_handler = RegisterEventHandler(
condition=UnlessCondition(use_namespace),
event_handler=OnProcessExit(
target_action=start_rviz_cmd,
on_exit=EmitEvent(event=Shutdown(reason='rviz exited'))))
exit_event_handler_namespaced = RegisterEventHandler(
condition=IfCondition(use_namespace),
event_handler=OnProcessExit(
target_action=start_namespaced_rviz_cmd,
on_exit=EmitEvent(event=Shutdown(reason='rviz exited'))))
# Create the launch description and populate
ld = LaunchDescription()
# Declare the launch options
ld.add_action(declare_namespace_cmd)
ld.add_action(declare_use_namespace_cmd)
ld.add_action(declare_rviz_config_file_cmd)
# Add any conditioned actions
ld.add_action(start_rviz_cmd)
ld.add_action(start_namespaced_rviz_cmd)
# Add other nodes and processes we need
ld.add_action(exit_event_handler)
ld.add_action(exit_event_handler_namespaced)
return ld

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<?xml version="1.0" encoding="UTF-8"?>
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<asset>
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<extra><technique profile="MAX3D"><frame_rate>30.000000</frame_rate></technique><technique profile="FCOLLADA"><start_time>0.000000</start_time><end_time>3.333333</end_time></technique></extra>
</visual_scene>
</library_visual_scenes>
<scene>
<instance_visual_scene url="#aws_DeskPortraitA_01_collision"></instance_visual_scene>
</scene>
</COLLADA>

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