ROS消息过滤器之 message_filters::Synchronizer 使用详解

2023-11-10 11:12
文章标签 使用 详解 过滤器 消息 message ros filters synchronizer

本文主要是介绍ROS消息过滤器之 message_filters::Synchronizer 使用详解，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

        在ROS中，当我们有多个传感器发布的数据需要同步时，message_filters::Synchronizer 是一个非常有用的工具。它可以确保多个消息在时间上是同步的，以便更有效地处理数据。

1.什么是ROS消息过滤器？

ROS消息过滤器是一种用于处理ROS消息的工具，允许我们对消息进行过滤、同步和组合。这对于在机器人感知中整合不同传感器数据或在控制中同步多个输入源非常重要。

2.message_filters::Synchronizer 简介

        message_filters::Synchronizer 是ROS中消息过滤器的一部分，专门用于同步多个消息。它可以确保多个发布者发布的消息在时间上是同步的，以便在回调函数中处理这些消息。

3.使用场景

        当你有多个传感器发布的数据，需要确保这些数据在同一时刻可用时，message_filters::Synchronizer 就派上用场了。例如，在处理相机图像和激光雷达扫描数据时，你可能希望它们在相同的时间戳上可用，以便更准确地进行感知。

4.示例代码

工程结构：

4.1 发布者节点 (image_publisher.cpp)

#include <ros/ros.h>
#include <sensor_msgs/Image.h>
#include <cv_bridge/cv_bridge.h>
#include <opencv2/highgui/highgui.hpp>#include <ros/ros.h>
#include <sensor_msgs/Image.h>
#include <sensor_msgs/PointCloud2.h>
#include <cv_bridge/cv_bridge.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>int main(int argc, char** argv)
{ros::init(argc, argv, "image_and_pointcloud_publisher");ros::NodeHandle nh;// 创建一个发布者，发布图像消息到 "/image_topic" 话题，缓存队列大小为 10ros::Publisher image_pub = nh.advertise<sensor_msgs::Image>("/image_topic", 10);// 创建一个发布者，发布点云消息到 "/pointcloud_topic" 话题，缓存队列大小为 10ros::Publisher pcl_pub = nh.advertise<sensor_msgs::PointCloud2>("/pointcloud_topic", 10);// 创建图像消息sensor_msgs::Image image_msg;// 设置图像消息的头部信息image_msg.header.stamp = ros::Time::now();image_msg.header.frame_id = "camera_frame";// 填充图像数据（这里假设你已经有一个图像数据，例如使用OpenCV加载的图像）cv::Mat image = cv::imread("/home/guo/Pictures/1.png", cv::IMREAD_COLOR);// 使用cv_bridge将OpenCV图像转换为ROS图像消息cv_bridge::CvImage cv_image;cv_image.image = image;cv_image.encoding = "bgr8"; // 8-bit, 3 channelimage_msg = *cv_image.toImageMsg();// 创建点云消息sensor_msgs::PointCloud2 pcl_msg;// 填充点云数据（这里假设你已经有一个点云数据，例如使用PCL库生成的点云）pcl::PointCloud<pcl::PointXYZI>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZI>);// Populate your point cloud data here...pcl::io::loadPCDFile("/home/guo/Downloads/pcd/1.pcd", *cloud);// 使用PCL库将点云转换为ROS点云消息pcl::toROSMsg(*cloud, pcl_msg);pcl_msg.header.stamp = ros::Time::now();pcl_msg.header.frame_id = "camera_frame";ros::Rate loop_rate(1); // 发布频率为1Hzwhile (ros::ok()){// 更新时间戳image_msg.header.stamp = ros::Time::now();pcl_msg.header.stamp = ros::Time::now();// 发布图像消息image_pub.publish(image_msg);// 发布点云消息pcl_pub.publish(pcl_msg);// 循环等待ros::spinOnce();loop_rate.sleep();}return 0;
}

4.2 订阅者节点 (synchronized_subscriber.cpp)

#include <ros/ros.h>
#include <sensor_msgs/Image.h>
#include <sensor_msgs/PointCloud2.h>
#include <message_filters/subscriber.h>
#include <message_filters/synchronizer.h>
#include <message_filters/sync_policies/approximate_time.h>void callback(const sensor_msgs::Image::ConstPtr& image_msg, const sensor_msgs::PointCloud2::ConstPtr& pcl_msg)
{// 处理同步的消息// image_msg 和 pcl_msg 在相同时间戳下ROS_INFO("Received synchronized the message of       image_msg at time %f", image_msg->header.stamp.toSec());ROS_INFO("Received synchronized the message of pcl_msg message at time %f", pcl_msg->header.stamp.toSec());ROS_INFO("------------------------------------------------------------------------");
}int main(int argc, char** argv)
{ros::init(argc, argv, "synchronized_subscriber");ros::NodeHandle nh;// 创建两个订阅者message_filters::Subscriber<sensor_msgs::Image> image_sub(nh, "/image_topic", 1);message_filters::Subscriber<sensor_msgs::PointCloud2> pcl_sub(nh, "/pointcloud_topic", 1);// 定义同步策略为 ApproximateTimetypedef message_filters::sync_policies::ApproximateTime<sensor_msgs::Image, sensor_msgs::PointCloud2> MySyncPolicy;// 创建同步器对象message_filters::Synchronizer<MySyncPolicy> sync(MySyncPolicy(10), image_sub, pcl_sub);// 注册回调函数sync.registerCallback(boost::bind(&callback, _1, _2));ros::spin();return 0;
}

 4.3 CMakeLists.txt

cmake_minimum_required(VERSION 3.0.2)
project(synchronizer)## Compile as C++11, supported in ROS Kinetic and newer
# add_compile_options(-std=c++11)## Find catkin macros and libraries
## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
## is used, also find other catkin packages
find_package(catkin REQUIRED COMPONENTScv_bridgeroscppsensor_msgsstd_msgsmessage_filterspcl_conversions
)find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
message(STATUS "version: ${OpenCV_VERSION}")find_package(PCL REQUIRED QUIET)
include_directories(${PCL_INCLUDE_DIRS})
## System dependencies are found with CMake's conventions
# find_package(Boost REQUIRED COMPONENTS system)## Uncomment this if the package has a setup.py. This macro ensures
## modules and global scripts declared therein get installed
## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
# catkin_python_setup()################################################
## Declare ROS messages, services and actions ##
################################################## To declare and build messages, services or actions from within this
## package, follow these steps:
## * Let MSG_DEP_SET be the set of packages whose message types you use in
##   your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
## * In the file package.xml:
##   * add a build_depend tag for "message_generation"
##   * add a build_depend and a exec_depend tag for each package in MSG_DEP_SET
##   * If MSG_DEP_SET isn't empty the following dependency has been pulled in
##     but can be declared for certainty nonetheless:
##     * add a exec_depend tag for "message_runtime"
## * In this file (CMakeLists.txt):
##   * add "message_generation" and every package in MSG_DEP_SET to
##     find_package(catkin REQUIRED COMPONENTS ...)
##   * add "message_runtime" and every package in MSG_DEP_SET to
##     catkin_package(CATKIN_DEPENDS ...)
##   * uncomment the add_*_files sections below as needed
##     and list every .msg/.srv/.action file to be processed
##   * uncomment the generate_messages entry below
##   * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)## Generate messages in the 'msg' folder
# add_message_files(
#   FILES
#   Message1.msg
#   Message2.msg
# )## Generate services in the 'srv' folder
# add_service_files(
#   FILES
#   Service1.srv
#   Service2.srv
# )## Generate actions in the 'action' folder
# add_action_files(
#   FILES
#   Action1.action
#   Action2.action
# )## Generate added messages and services with any dependencies listed here
# generate_messages(
#   DEPENDENCIES
#   sensor_msgs#   std_msgs
# )################################################
## Declare ROS dynamic reconfigure parameters ##
################################################## To declare and build dynamic reconfigure parameters within this
## package, follow these steps:
## * In the file package.xml:
##   * add a build_depend and a exec_depend tag for "dynamic_reconfigure"
## * In this file (CMakeLists.txt):
##   * add "dynamic_reconfigure" to
##     find_package(catkin REQUIRED COMPONENTS ...)
##   * uncomment the "generate_dynamic_reconfigure_options" section below
##     and list every .cfg file to be processed## Generate dynamic reconfigure parameters in the 'cfg' folder
# generate_dynamic_reconfigure_options(
#   cfg/DynReconf1.cfg
#   cfg/DynReconf2.cfg
# )###################################
## catkin specific configuration ##
###################################
## The catkin_package macro generates cmake config files for your package
## Declare things to be passed to dependent projects
## INCLUDE_DIRS: uncomment this if your package contains header files
## LIBRARIES: libraries you create in this project that dependent projects also need
## CATKIN_DEPENDS: catkin_packages dependent projects also need
## DEPENDS: system dependencies of this project that dependent projects also need
catkin_package(
#  INCLUDE_DIRS include
#  LIBRARIES synchronizer
#  CATKIN_DEPENDS cv_bridge roscpp sensor_msgs std_msgs
#  DEPENDS system_lib
# DEPENDS OpenCV
)###########
## Build ##
############# Specify additional locations of header files
## Your package locations should be listed before other locations
include_directories(
# include${catkin_INCLUDE_DIRS}
)## Declare a C++ library
# add_library(image_publisher
#   src/image_publisher.cpp
# )## Add cmake target dependencies of the library
## as an example, code may need to be generated before libraries
## either from message generation or dynamic reconfigure
# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})## Declare a C++ executable
## With catkin_make all packages are built within a single CMake context
## The recommended prefix ensures that target names across packages don't collide
add_executable(image_publisher /home/guo/Downloads/syn_ws/src/synchronizer/src/image_publisher.cpp)
add_executable(synchronized_subscriber /home/guo/Downloads/syn_ws/src/synchronizer/src/synchronized_subscriber.cpp)## Rename C++ executable without prefix
## The above recommended prefix causes long target names, the following renames the
## target back to the shorter version for ease of user use
## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")## Add cmake target dependencies of the executable
## same as for the library above
# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})## Specify libraries to link a library or executable target against
target_link_libraries(image_publisher${catkin_LIBRARIES}${OpenCV_INCLUDE_DIRS}${PCL_INCLUDE_DIRS}
)target_link_libraries(synchronized_subscriber${catkin_LIBRARIES}
)#############
## Install ##
############## all install targets should use catkin DESTINATION variables
# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html## Mark executable scripts (Python etc.) for installation
## in contrast to setup.py, you can choose the destination
# catkin_install_python(PROGRAMS
#   scripts/my_python_script
#   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
# )## Mark executables for installation
## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_executables.html
# install(TARGETS ${PROJECT_NAME}_node
#   RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
# )## Mark libraries for installation
## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_libraries.html
# install(TARGETS ${PROJECT_NAME}
#   ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
#   LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
#   RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}
# )## Mark cpp header files for installation
# install(DIRECTORY include/${PROJECT_NAME}/
#   DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
#   FILES_MATCHING PATTERN "*.h"
#   PATTERN ".svn" EXCLUDE
# )## Mark other files for installation (e.g. launch and bag files, etc.)
# install(FILES
#   # myfile1
#   # myfile2
#   DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
# )#############
## Testing ##
############### Add gtest based cpp test target and link libraries
# catkin_add_gtest(${PROJECT_NAME}-test test/test_synchronizer.cpp)
# if(TARGET ${PROJECT_NAME}-test)
#   target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
# endif()## Add folders to be run by python nosetests
# catkin_add_nosetests(test)

4.4 launch文件

<launch><!-- Start the image_publisher_node --><node name="synchronizer1" pkg="synchronizer" type="image_publisher" output="screen"/><!-- Start the synchronized_subscriber_node --><node name="synchronizer2" pkg="synchronizer" type="synchronized_subscriber" output="screen"/></launch>

4.5 代码解释

  • 引入必要的ROS和消息过滤器头文件。
  • 定义回调函数 callback，用于处理同步的图像和激光雷达数据。
  • 在 main 函数中创建 message_filters::Subscriber 对象，分别订阅相机图像和激光雷达扫描数据。
  • 使用 message_filters::sync_policies::ApproximateTime 创建 message_filters::Synchronizer 对象，设置时间同步策略为近似同步。
  • 注册回调函数到 Synchronizer 对象中，它将在图像和激光雷达数据近似同步时调用。

5. 运行和测试

        确保ROS环境已经启动，然后运行launch文件：

        运行结果：

图像和点云的时间辍实现同步。 

 

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