ros消息时间同步与回调

转载自http://blog.csdn.net/zyh821351004/article/details/47758433

方式一: 全局变量形式  : TimeSynchronizer

步骤:

1.   message_filter ::subscriber 分别订阅不同的输入topic

2.  TimeSynchronizer<Image,CameraInfo>   定义时间同步器;

3.  sync.registerCallback      同步回调

4.  void callback(const ImageConstPtr&image, const CameraInfoConstPtr& cam_info)     带多消息的消息同步自定义回调函数

相应的API  message_filters::TimeSynchronizer

//wiki参考demo http://wiki.ros.org/message_filters
#include <message_filters/subscriber.h>
#include <message_filters/time_synchronizer.h>
#include <sensor_msgs/Image.h>
#include <sensor_msgs/CameraInfo.h>

using namespace sensor_msgs;
using namespace message_filters;

void callback(const ImageConstPtr& image, const CameraInfoConstPtr& cam_info)  //回调中包含多个消息
{
  // Solve all of perception here...
}

int main(int argc, char** argv)
{
  ros::init(argc, argv, "vision_node");

  ros::NodeHandle nh;

  message_filters::Subscriber<Image> image_sub(nh, "image", );             // topic1 输入
  message_filters::Subscriber<CameraInfo> info_sub(nh, "camera_info", );   // topic2 输入
  TimeSynchronizer<Image, CameraInfo> sync(image_sub, info_sub, );       // 同步
  sync.registerCallback(boost::bind(&callback, _1, _2));                   // 回调

  ros::spin();

  return ;
}
// 

参考连接:http://wiki.ros.org/message_filters

方式二: 类成员的形式  message_filters::Synchronizer

说明: 我用 TimeSynchronizer 改写成类形式中间出现了一点问题.后就改写成message_filters::Synchronizer的形式.

1. 头文件

#include <message_filters/subscriber.h>
#include <message_filters/synchronizer.h>
#include <message_filters/sync_policies/approximate_time.h>

2. 定义消息同步机制

typedef message_filters::sync_policies::ApproximateTime<nav_msgs::Odometry,sensor_msgs::Image> slamSyncPolicy;

3. 定义类成员变量

    message_filters::Subscriber<nav_msgs::Odometry>* odom_sub_ ;             // topic1 输入
    message_filters::Subscriber<sensor_msgs::Image>* img_sub_;   // topic2 输入
    message_filters::Synchronizer<slamSyncPolicy>* sync_;

4.类构造函数中开辟空间new

    odom_sub_ = new message_filters::Subscriber<nav_msgs::Odometry>(ar_handle, "/odom", );
    img_sub_  = new message_filters::Subscriber<sensor_msgs::Image>(ar_handle, "/usb_cam/image_raw", );

    sync_ = new  message_filters::Synchronizer<slamSyncPolicy>(slamSyncPolicy(), *odom_sub_, *img_sub_);
    sync_->registerCallback(boost::bind(&QrSlam::combineCallback,this, _1, _2));

5. 类成员函数回调处理

void QrSlam::combineCallback(const nav_msgs::Odometry::ConstPtr& pOdom, const sensor_msgs::ImageConstPtr& pImg)  //回调中包含多个消息
{
    //TODO
    fStampAll<<pOdom->header.stamp<<"    "<<pImg->header.stamp<<endl;
    getOdomData(pOdom);                   //
    is_img_update_ = getImgData(pImg);    // 像素值
    cout << "stamp x y theta v w " << robot_odom_.stamp<<" "<<robot_odom_.x << " "<< robot_odom_.y << " " << robot_odom_.theta
         << " " << robot_odom_.v << " " << robot_odom_.w << std::endl;
    fOdom << "stamp x y theta v w " << robot_odom_.stamp<<" "<<robot_odom_.x << " "<< robot_odom_.y << " " << robot_odom_.theta
          << " " << robot_odom_.v << " " << robot_odom_.w << std::endl;
    pixDataToMetricData();
    static bool FINISH_INIT_ODOM_STATIC = false;
    if(FINISH_INIT_ODOM_STATIC)
    {
        ekfslam(robot_odom_);
    }
    else if(is_img_update_)
    {
        if(addInitVectorFull())
        {
            computerCoordinate();
            FINISH_INIT_ODOM_STATIC = true;
        }
    }
}