系统是Ubuntu22.04，之前安装好了ROS 2 Humble Hawksbill，现在测试一下环境：
1、准备工作
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| # 确保系统已经更新
sudo apt update
sudo apt upgrade
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2、验证ROS2的安装与环境配置
检查ROS2版本
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| # 用以下命令来检查当前使用的ROS2发行版名称
echo $ROS_DISTRO
# 配置正确则输出所安装的ROS2版本，如：humble
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查看ROS2安装路径中的版本信息
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| lures@lures-Redmi-G-Pro-2024:~$ grep "version" /opt/ros/humble/.rosinstall
grep: /opt/ros/humble/.rosinstall: No such file or directory
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缺少.rosinstall文件：/opt/ros/humble/.rosinstall文件不存在是正常的，因为这个文件通常在源代码安装(从源码编译)的情况下才存在。如果你是通过Debian包管理器(例如apt)安装的ROS2，这个文件通常不会存在
查看ROS2的已安装包
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| lures@lures-Redmi-G-Pro-2024:~$ ros2 pkg list
action_msgs
action_tutorials_cpp
action_tutorials_interfaces
action_tutorials_py
actionlib_msgs
ament_cmake
ament_cmake_auto
ament_cmake_copyright
ament_cmake_core
ament_cmake_cppcheck
ament_cmake_cpplint
ament_cmake_export_definitions
ament_cmake_export_dependencies
ament_cmake_export_include_directories
ament_cmake_export_interfaces
ament_cmake_export_libraries
ament_cmake_export_link_flags
ament_cmake_export_targets
ament_cmake_flake8
ament_cmake_gen_version_h
ament_cmake_gmock
ament_cmake_gtest
ament_cmake_include_directories
ament_cmake_libraries
ament_cmake_lint_cmake
ament_cmake_pep257
ament_cmake_pytest
ament_cmake_python
ament_cmake_ros
ament_cmake_target_dependencies
ament_cmake_test
ament_cmake_uncrustify
ament_cmake_version
ament_cmake_xmllint
ament_copyright
ament_cppcheck
ament_cpplint
ament_flake8
ament_index_cpp
ament_index_python
ament_lint
ament_lint_auto
ament_lint_cmake
ament_lint_common
ament_package
ament_pep257
ament_uncrustify
ament_xmllint
angles
builtin_interfaces
class_loader
common_interfaces
composition
composition_interfaces
console_bridge_vendor
cv_bridge
demo_nodes_cpp
demo_nodes_cpp_native
demo_nodes_py
depthimage_to_laserscan
desktop
diagnostic_msgs
domain_coordinator
dummy_map_server
dummy_robot_bringup
dummy_sensors
eigen3_cmake_module
example_interfaces
examples_rclcpp_minimal_action_client
examples_rclcpp_minimal_action_server
examples_rclcpp_minimal_client
examples_rclcpp_minimal_composition
examples_rclcpp_minimal_publisher
examples_rclcpp_minimal_service
examples_rclcpp_minimal_subscriber
examples_rclcpp_minimal_timer
examples_rclcpp_multithreaded_executor
examples_rclpy_executors
examples_rclpy_minimal_action_client
examples_rclpy_minimal_action_server
examples_rclpy_minimal_client
examples_rclpy_minimal_publisher
examples_rclpy_minimal_service
examples_rclpy_minimal_subscriber
fastrtps_cmake_module
geometry2
geometry_msgs
image_geometry
image_tools
image_transport
interactive_markers
intra_process_demo
joy
kdl_parser
keyboard_handler
laser_geometry
launch
launch_ros
launch_testing
launch_testing_ament_cmake
launch_testing_ros
launch_xml
launch_yaml
libcurl_vendor
libstatistics_collector
libyaml_vendor
lifecycle
lifecycle_msgs
logging_demo
map_msgs
message_filters
nav_msgs
orocos_kdl_vendor
osrf_pycommon
pcl_conversions
pcl_msgs
pendulum_control
pendulum_msgs
pluginlib
pybind11_vendor
python_cmake_module
python_qt_binding
qt_dotgraph
qt_gui
qt_gui_cpp
qt_gui_py_common
quality_of_service_demo_cpp
quality_of_service_demo_py
rcl
rcl_action
rcl_interfaces
rcl_lifecycle
rcl_logging_interface
rcl_logging_spdlog
rcl_yaml_param_parser
rclcpp
rclcpp_action
rclcpp_components
rclcpp_lifecycle
rclpy
rcpputils
rcutils
resource_retriever
rmw
rmw_dds_common
rmw_fastrtps_cpp
rmw_fastrtps_shared_cpp
rmw_implementation
rmw_implementation_cmake
robot_state_publisher
ros2action
ros2bag
ros2cli
ros2cli_common_extensions
ros2component
ros2doctor
ros2interface
ros2launch
ros2lifecycle
ros2multicast
ros2node
ros2param
ros2pkg
ros2run
ros2service
ros2topic
ros_base
ros_core
ros_environment
ros_workspace
rosbag2
rosbag2_compression
rosbag2_compression_zstd
rosbag2_cpp
rosbag2_interfaces
rosbag2_py
rosbag2_storage
rosbag2_storage_default_plugins
rosbag2_transport
rosgraph_msgs
rosidl_adapter
rosidl_cli
rosidl_cmake
rosidl_default_generators
rosidl_default_runtime
rosidl_generator_c
rosidl_generator_cpp
rosidl_generator_py
rosidl_parser
rosidl_runtime_c
rosidl_runtime_cpp
rosidl_runtime_py
rosidl_typesupport_c
rosidl_typesupport_cpp
rosidl_typesupport_fastrtps_c
rosidl_typesupport_fastrtps_cpp
rosidl_typesupport_interface
rosidl_typesupport_introspection_c
rosidl_typesupport_introspection_cpp
rpyutils
rqt_action
rqt_bag
rqt_bag_plugins
rqt_common_plugins
rqt_console
rqt_graph
rqt_gui
rqt_gui_cpp
rqt_gui_py
rqt_image_view
rqt_msg
rqt_plot
rqt_publisher
rqt_py_common
rqt_py_console
rqt_reconfigure
rqt_service_caller
rqt_shell
rqt_srv
rqt_topic
rttest
rviz2
rviz_assimp_vendor
rviz_common
rviz_default_plugins
rviz_ogre_vendor
rviz_rendering
sdl2_vendor
sensor_msgs
sensor_msgs_py
shape_msgs
shared_queues_vendor
spdlog_vendor
sqlite3_vendor
sros2
sros2_cmake
statistics_msgs
std_msgs
std_srvs
stereo_msgs
tango_icons_vendor
teleop_twist_joy
teleop_twist_keyboard
tf2
tf2_bullet
tf2_eigen
tf2_eigen_kdl
tf2_geometry_msgs
tf2_kdl
tf2_msgs
tf2_py
tf2_ros
tf2_ros_py
tf2_sensor_msgs
tf2_tools
tinyxml2_vendor
tinyxml_vendor
tlsf
tlsf_cpp
topic_monitor
tracetools
trajectory_msgs
turtlesim
uncrustify_vendor
unique_identifier_msgs
urdf
urdf_parser_plugin
visualization_msgs
yaml_cpp_vendor
zstd_vendor
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会列出当前已安装的所有ROS2软件包，说明ROS2环境已经安装并配置成功
验证ROS2功能
可以进行下图所示的功能测试：
显示：
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| lures@lures-Redmi-G-Pro-2024:~$ ros2 topic list
/chatter
/parameter_events
/rosout
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3、安装Gazebo
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| # 安装Gazebo相关包
sudo apt update
sudo apt install ros-humble-gazebo-ros-pkgs ros-humble-gazebo-ros ros-humble-ros-gz-sim
# 启动gazebo的方式
ign gazebo
# 或者对于ROS2和Gazebo集成的情况，可以使用ROS2的launch文件来启动Gazebo仿真
# 分别启动Gazebo的服务器端和客户端
ros2 launch gazebo_ros gzserver.launch.py
ros2 launch gazebo_ros gzclient.launch.py
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也可以在管理器中找到对应个的应用图标打开：
4、安装NVIDIA驱动和CUDA
此处，我已经在配置深度学习环境时配置了，当前PyTorch和Tensorflow支持的CUDA版本是11.8，所以自己的驱动及下载的CUDA及相关工具包注意版本要一致，要不很麻烦～
通过下面命令查看GPU和CUDA版本信息，说输出如下图类似，则说明NVIDIA驱动和CUDA安装成功
5、配置Gazebo使用GPU加速
-v 4使Gazebo以详细模式启动，这样可以在终端中看到Gazebo的加载日志，启动后，查看日志中是否有NVIDIA GPU的信息。同时在另一个窗口运行nvidia-smi，检查GPU使用情况：
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| watch -n 1 nvidia-smi
# 会每秒刷新一次 GPU 使用情况。如果 Gazebo 正在使用 GPU，你应该能够看到 GPU 的使用率上升。
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6、使用Gazebo和ROS2的简单测试
Gazebo 服务端（gzserver）成功启动：ROS 2 与 Gazebo 集成部分没有报错，gzserver 进程已经运行，并输出了进程 ID。
ROS 2 主题列表：列出了当前活跃的 ROS 2 主题，显示了一些基本的 ROS 2 主题（如 /clock、/rosout 等）。不过，没有看到与 Gazebo 仿真模型、传感器数据相关的主题。
新建一个demo.sdf文件，文件内容为：
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| <?xml version="1.0" ?>
<sdf version="1.6">
<model name="test_camera_box">
<static>false</static>
<link name="link">
<inertial>
<mass>1.0</mass>
</inertial>
<visual name="visual">
<geometry>
<box>
<size>0.5 0.5 0.5</size>
</box>
</geometry>
<material>
<ambient>1 0 0 1</ambient>
<diffuse>1 0 0 1</diffuse>
</material>
</visual>
<collision name="collision">
<geometry>
<box>
<size>0.5 0.5 0.5</size>
</box>
</geometry>
</collision>
<sensor name="camera" type="camera">
<camera>
<horizontal_fov>1.047</horizontal_fov>
<image>
<width>640</width>
<height>480</height>
<format>R8G8B8</format>
</image>
<clip>
<near>0.1</near>
<far>100</far>
</clip>
</camera>
<always_on>true</always_on>
<update_rate>30</update_rate>
<plugin name="camera_controller" filename="libgazebo_ros_camera.so">
<ros>
<namespace>/my_camera</namespace>
<remapping>image_raw:=/camera/image_raw</remapping>
</ros>
<camera_name>camera</camera_name>
</plugin>
</sensor>
</link>
</model>
</sdf>
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格式化SDF内容为命令行字符串：XML内容的双引号需要进行转义：
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| ros2 service call /spawn_entity gazebo_msgs/SpawnEntity "{
name: 'test_camera_box',
xml: '<?xml version=\"1.0\" ?><sdf version=\"1.6\"><model name=\"test_camera_box\"><static>false</static><link name=\"link\"><inertial><mass>1.0</mass></inertial><visual name=\"visual\"><geometry><box><size>0.5 0.5 0.5</size></box></geometry><material><ambient>1 0 0 1</ambient><diffuse>1 0 0 1</diffuse></material></visual><collision name=\"collision\"><geometry><box><size>0.5 0.5 0.5</size></box></geometry></collision><sensor name=\"camera\" type=\"camera\"><camera><horizontal_fov>1.047</horizontal_fov><image><width>640</width><height>480</height><format>R8G8B8</format></image><clip><near>0.1</near><far>100</far></clip></camera><always_on>true</always_on><update_rate>30</update_rate><plugin name=\"camera_controller\" filename=\"libgazebo_ros_camera.so\"><ros><namespace>/my_camera</namespace><remapping>image_raw:=/camera/image_raw</remapping></ros><camera_name>camera</camera_name></plugin></sensor></link></model></sdf>',
robot_namespace: '',
initial_pose: { position: { x: 0.0, y: 0.0, z: 0.5 }, orientation: { w: 1.0 } },
reference_frame: 'world'
}"
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启动Gazebo的服务端和客户端，确保启动
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| # 这样会启动 Gazebo 的图形界面和物理模拟服务
ros2 launch gazebo_ros gzserver.launch.py
ros2 launch gazebo_ros gzclient.launch.py
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在终端运行之前的XML命令，显示结果：
如果希望查看摄像头的图像输出，可以使用rqt_image_view，命令如下：
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| ros2 run rqt_image_view rqt_image_view
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在 rqt_image_view 界面中选择 /my_camera/image_raw 主题，能看到相机的实时图像。
