vio 不同数据对齐的相关处理---以vins-mono为例

1、首先订阅IMU、图像信息

    ros::Subscriber sub_imu = n.subscribe(IMU_TOPIC, 2000, imu_callback, ros::TransportHints().tcpNoDelay());
    ros::Subscriber sub_image = n.subscribe("/feature_tracker/feature", 2000, feature_callback);

2、在imu_callback、feature_callback中将数据压入buffer

    m_buf.lock();
    imu_buf.push(imu_msg);
    m_buf.unlock();
    con.notify_one();

    m_buf.lock();
    feature_buf.push(feature_msg);
    m_buf.unlock();
    con.notify_one();

 3、在measurements函数中对两个buffer的数据进行对齐，大致地找到一帧图像左右的imu

    while (true)
    {
        if (imu_buf.empty() || feature_buf.empty())
            return measurements;

        if (!(imu_buf.back()->header.stamp.toSec() > feature_buf.front()->header.stamp.toSec() + estimator.td))
        {
            //ROS_WARN("wait for imu, only should happen at the beginning");
            sum_of_wait++;
            return measurements;
        }
//总的趋势来看，img是夹杂在imu数据中间的
        if (!(imu_buf.front()->header.stamp.toSec() < feature_buf.front()->header.stamp.toSec() + estimator.td))
        {
            ROS_WARN("throw img, only should happen at the beginning");
            feature_buf.pop();
            continue;
        }
        sensor_msgs::PointCloudConstPtr img_msg = feature_buf.front();
        feature_buf.pop();

        std::vector IMUs;
        while (imu_buf.front()->header.stamp.toSec() < img_msg->header.stamp.toSec() + estimator.td)
        {
            IMUs.emplace_back(imu_buf.front());
            imu_buf.pop();
        }
        IMUs.emplace_back(imu_buf.front());//IMU的数量要比图像的数量多1
        if (IMUs.empty())
            ROS_WARN("no imu between two image");
        measurements.emplace_back(IMUs, img_msg);
    }
    return measurements;
}

 

4、在得到的测量中，对IMU数据预积分处理（可能需要线性差值处理），针对图像数据，进行初始化，或者正常的里程计解算。