ros下xtion用法

xtion用openni2_launch openni2.launch就可以打开，但是在使用过程中有一些定制性问题：

首先弄清openni2_launch 中一些topic都是什么意思

http://wiki.ros.org/depth_image_proc

关于depthmap是米制还是毫米制：

All nodelets (besides convert_metric) in this package support both standard floating point depth images and OpenNI-specific uint16 depth images. Thus when working with OpenNI cameras (e.g. the Kinect), you can save a few CPU cycles by using the uint16 raw topics instead of the float topics.

/depth/image_raw是uint16格式

/depth_registered/image是CV32FC1

关于topic中rect解释：

http://wiki.ros.org/rgbd_launch

depth_processing (bool, default: true)

Given the raw depth image, rectifies it, converts both the raw and rectified images to metric format (uint16 -> float), and produces a pointcloud. Requires depth/image_raw. Produces depth/image_rect_raw (rectified), depth/image (metric), depth/image_rect (rectified, metric), depth/points (pointcloud).

depth_registered_processing (bool, default: true)

Generates a registered RGBD pointcloud from the device data (requires rgb_processing to be enabled). A pointcloud can be generated through a software registration pipeline (sw_registered_processing = true, used when depth_registration for device driver is set to false ) by registering the depth image from the depth frame to an RGB frame and merging with the RGB image. If software registration is being used, depth_processing needs to be enabled. Alternatively, the device can be directly asked to generate a registered depth image in the RGB frame with can be merged with the RGB Image through the hardware registration pipeline (hw_registered_processing = true, used when depth_registration for device driver is set to true)

在使用过程中出现了

/camera/depth_registered/sw_registered/image_rect_raw

图像显示之后出现很多不规则横杠和竖杠

更改为hw_registered模式就好了

具体更改openni2_launch openni2.launch里

<arg name="depth_registration" default="true" />就好了

关于怎么保存pcd文件

ros里提供了一个包 pcl_ros

使用pointcloud_to_pcd

以下是一个launch file

<launch>

  <arg name="viewer" default = "true" />

  <arg name="image_saver" default="false" />

  <arg name="pcd_saver" default = "false" />

  <node pkg="image_view" type="image_view" respawn="false" name="rgb_image_viewer" output="screen" if="$(arg viewer)">

   <remap from="image" to="/camera/rgb/image_rect_color"/>

  </node>

  <node pkg="image_view" type="image_view" respawn="false" name="depth_image_viewer" output="screen" if="$(arg viewer)">

  <remap from="image" to="/camera/depth_registered/hw_registered/image_rect"/>

  </node>

  <include file="$(find openni2_launch)/launch/openni2.launch" />

  <node pkg="pioneer_zed" type="test_sycronizer" name="rgb_depth_sycronizer"  if="$(arg image_saver)"/>

  <node pkg="pcl_ros" type="pointcloud_to_pcd" name="pointcloud_to_pcd" output="screen" if="$(arg pcd_saver)">

    <remap from="input" to="/camera/depth_registered/points"/>

    <param name="prefix" value="/home/ubuntu/Workspaces/dataset/homemade/pcd/vel_" />

  </node>

</launch>

rgb和depth同步问题

这个可以用message filter来实现

下面是一个程序实现：

#include <ros/ros.h>

#include "RGBDImgsSycronizer.h"

int main(int argc, char** argv)

{

  ros::init(argc, argv, "tf_broadcaster");

  ros::NodeHandle nh;

  RGBDImgsSycronizer test_sycronizer(nh,"/camera/rgb/image_rect_color","/camera/depth_registered/hw_registered/image_rect_raw","/home/ubuntu/Workspaces/dataset/homemade");

  ros::spin();

}

#include "RGBDImgsSycronizer.h"

#include <boost/bind/bind.hpp>

RGBDImgsSycronizer::~RGBDImgsSycronizer()

{

    fs.release();

}

RGBDImgsSycronizer::RGBDImgsSycronizer(ros::NodeHandle& nh, string imageColorTopic, string imageDepthTopic,string storeDirectory):

    nh_(nh),

    imageDepth_sub(nh_, imageDepthTopic, ),

    imageColor_sub(nh_, imageColorTopic, ),

    sync(MySyncPolicy(), imageColor_sub, imageDepth_sub),

    storePath(storeDirectory),

    fs(storePath+"/depthData.yml", FileStorage::WRITE)

{

    ROS_INFO("RGBDImgsSycronizer constrcting");

    // ApproximateTime takes a queue size as its constructor argument, hence MySyncPolicy(10)

    sync.registerCallback(boost::bind(&RGBDImgsSycronizer::call_back, this,_1, _2));

    data_ready = false;

}

//注意这里需要加const

void RGBDImgsSycronizer::call_back(const ImageConstPtr &imageColor, const ImageConstPtr &imageDepth)

{

    static int num = ;

    ROS_INFO("recive");

    cv_bridge::CvImagePtr imageColorPtr = cv_bridge::toCvCopy(imageColor);

    OpencvimageColor = imageColorPtr->image;

    cv_bridge::CvImagePtr imageDepthPtr = cv_bridge::toCvCopy(imageDepth);

    OpencvImageDepth = imageDepthPtr->image;

    boost::format imageColorStr(storePath+"/color/imageColor%d.png"),imageDepthStr(storePath+"/depth/imageDepth%d.png");

    imageColorStr%num;

    imageDepthStr%num;

    string strToDisplay = imageColorStr.str();

    if(!OpencvimageColor.empty())

        ROS_INFO("%s",strToDisplay.c_str());

    //store color image

    imwrite(imageColorStr.str(),OpencvimageColor);

    //store depth data

    boost::format imageDepthDataStr("imageDepthData%d");

    imageDepthDataStr%num;

    fs<<imageDepthDataStr.str()<<OpencvImageDepth;

    //store depth image

    double* minVal = new double, *maxVal = new double;

    Mat OpencvImageDepthImage;

    OpencvImageDepth.copyTo(OpencvImageDepthImage);

    minMaxIdx(OpencvImageDepthImage,minVal,maxVal);

    ROS_INFO("OpencvImageDepthImage type:%d ",OpencvImageDepthImage.type());

    if(maxVal==NULL)

    ROS_INFO(" maxVal maxVal");

    MatIterator_<float> it, end;

    for( it = OpencvImageDepthImage.begin<float>(), end = OpencvImageDepthImage.end<float>(); it != end; ++it)

        *it = ((*it)/(*maxVal)*);

    Mat OpencvImageDepthImage8U;

    OpencvImageDepthImage.convertTo(OpencvImageDepthImage8U,CV_8UC1);

    imwrite(imageDepthStr.str(),OpencvImageDepthImage8U);

    num++;

    delete minVal;

    delete maxVal;

}

bool RGBDImgsSycronizer::is_data_ready()

{

    if(data_ready)

        return true;

    else

        return false;

}

巴特西

ros下xtion用法

最新文章

热门文章