PCL octree std::bad_alloc c++

Question

我正在使用 PCl 库来压缩激光雷达数据。然后通过 ROS 网络将这些数据与自定义消息一起发送。为此，我有一个压缩节点和一个解压缩节点。如果我运行压缩节点，一切都会按预期工作。然而，当调用 decodePointCloud() 函数时，解压缩节点会给出一个 std::bad_alloc。

为了调试它，我将解压的代码复制到压缩程序中。当我现在运行压缩程序时，它可以工作。激光雷达数据首先被压缩并在同一个文件中解压缩。我用可视化软件rviz验证了这一点。

为什么我在同一个节点解压可以，但是在单独的节点解压就不行了？我一开始以为是因为内存不足，但是当我在同一个节点解压数据的时候就可以了。我认为这应该占用大约相同数量的内存。

我在具有 Ubuntu 18.04、5gb 内存和 4 个处理器的 VM 上运行这两个程序。

压缩代码：

#include <stdint.h>
#include <ros/ros.h>
// PCL specific includes
#include <sensor_msgs/PointCloud2.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>


#include <inttypes.h>
#include <pcl/compression/octree_pointcloud_compression.h>
#include <stdio.h>
#include <sstream>
#include <stdlib.h>
#include <chrono>
#include <string>
#include <std_msgs/String.h>
#include <bitset>
#include <std_msgs/UInt8MultiArray.h>
#include <stdint.h>
#include <iostream>
#include <vector>
#include <iterator>

//blob message
#include "my_pcl_tutorial/Blob.h"

ros::Publisher pub;

pcl::io::OctreePointCloudCompression<pcl::PointXYZRGBA>* PointCloudEncoder;



void 
cloud_cb (const sensor_msgs::PointCloud2ConstPtr& input)
{
  // Create a container for the data.
  std::string output;
  std_msgs::String outputString;

  //convert to pointxyzrgba type
  pcl::PCLPointCloud2 pcl_pc2;
  pcl::PointCloud<pcl::PointXYZRGBA>::Ptr temp_cloud (new pcl::PointCloud<pcl::PointXYZRGBA>);//convert to pointer to satisfy function requirement
  pcl_conversions::toPCL(*input, pcl_pc2);
  pcl::fromPCLPointCloud2(pcl_pc2, *temp_cloud); 

  // stringstream to store compressed point cloud
  std::stringstream compressedData; 

  // compress point cloud
  PointCloudEncoder->encodePointCloud (temp_cloud, compressedData);


  compressedData.seekg(0,ios::end);
  int size = compressedData.tellg();
  compressedData.seekg(0,ios::beg);
  std::cout<<size<<std::endl;


  char * buffer = new char[size];

  compressedData.read(buffer,size);

  uint8_t * tempor = reinterpret_cast<uint8_t *>(buffer);
  std::vector<unsigned char> v(tempor, tempor + size);
  std::cout<<"Size: "<<v.size()<<std::endl;


  my_pcl_tutorial::Blob blobmsg;
  blobmsg.data=v;
  blobmsg.size=size;

  sensor_msgs::PointCloud2 pointcloudheader;
  pointcloudheader = *input;
  blobmsg.header = pointcloudheader.header;


//////////////////////////////////////////////
/*
  //converting back, used for testing
  std::stringstream test25;

  std::vector<unsigned char> v2(blobmsg.data);
std::cout<<"Size2: "<<v2.size()<<std::endl;
std::cout<<"Size of message: "<<blobmsg.size<<std::endl;

  std::copy(v2.begin(), v2.end(), std::ostream_iterator<unsigned char>(test25));
std::cout<<"debug"<<std::endl;

  test25.seekg(0,ios::end);
  int size2 = test25.tellg();
  test25.seekg(0,ios::beg);
  std::cout<<size2<<std::endl;

  pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloudOut (new pcl::PointCloud<pcl::PointXYZRGBA> ());
  //decompress
  PointCloudDecoder->decodePointCloud (test25, cloudOut);




  sensor_msgs::PointCloud2 outputmessage;
  std::cout<<"Convert to right format now .."<<std::endl;
  //save header info since toROSmsg throws away this information
  //convert to pointcloud2
  pcl::toROSMsg(*cloudOut, outputmessage);
  outputmessage.header = blobmsg.header;
  std::cout<<outputmessage.header<<std::endl;

/**/

/////////////////////////////


  // Publish the data.
  pub.publish (blobmsg);
}

int
main (int argc, char** argv)
{
  // Initialize ROS
  ros::init (argc, argv, "my_pcl_tutorial");
  ros::NodeHandle nh;


  //\\
  //setup compression algorithm


  bool showStatistics = false;

  pcl::io::compression_Profiles_e compressionProfile = pcl::io::LOW_RES_ONLINE_COMPRESSION_WITHOUT_COLOR;

  // instantiate point cloud compression for encoding and decoding
  PointCloudEncoder = new pcl::io::OctreePointCloudCompression<pcl::PointXYZRGBA> (compressionProfile, showStatistics);
  //\\



  // Create a ROS subscriber for the input point cloud
  ros::Subscriber sub = nh.subscribe ("velodyne_points", 1, cloud_cb);

  // Create a ROS publisher for the output point cloud
  pub = nh.advertise<my_pcl_tutorial::Blob> ("velodyne_points/compressed", 1);

  // Spin
  ros::spin ();

  delete(PointCloudEncoder);
}

解压代码：

#include <stdint.h>
#include <ros/ros.h>
// PCL specific includes
#include <sensor_msgs/PointCloud2.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>

#include <inttypes.h>
#include <pcl/compression/octree_pointcloud_compression.h>
#include <stdio.h>
#include <sstream>
#include <stdlib.h>
#include <chrono>
#include <string>
#include <std_msgs/String.h>
#include <iostream>
#include <cstring>


#include <bitset>
#include <std_msgs/UInt8MultiArray.h>
#include <stdint.h>
#include <iostream>
#include <vector>
#include <iterator>

//blob message
//#include "decompression/Blob.h"
#include <my_pcl_tutorial/Blob.h>

ros::Publisher pub;


pcl::io::OctreePointCloudCompression<pcl::PointXYZRGBA>* PointCloudDecoder;




void 
cloud_cb (const my_pcl_tutorial::Blob& input)
{


  //converting back, used for testing
  std::stringstream test25;

  std::vector<unsigned char> v2(input.data);
std::cout<<"Size2: "<<v2.size()<<std::endl;
std::cout<<"Size of message: "<<input.size<<std::endl;

  std::copy(v2.begin(), v2.end(), std::ostream_iterator<unsigned char>(test25));
std::cout<<"debug"<<std::endl;

  test25.seekg(0,ios::end);
  int size2 = test25.tellg();
  test25.seekg(0,ios::beg);
  std::cout<<size2<<std::endl;

  pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloudOut (new pcl::PointCloud<pcl::PointXYZRGBA> ());
  //decompress
  PointCloudDecoder->decodePointCloud (test25, cloudOut);




  sensor_msgs::PointCloud2 outputmessage;
  std::cout<<"Convert to right format now .."<<std::endl;
  //save header info since toROSmsg throws away this information
  //convert to pointcloud2
  pcl::toROSMsg(*cloudOut, outputmessage);
  outputmessage.header = input.header;
  std::cout<<outputmessage.header<<std::endl;

  pub.publish(outputmessage);
}

int
main (int argc, char** argv)
{
  // Initialize ROS
  ros::init (argc, argv, "decompressLidar");
  ros::NodeHandle nh;

  //\\
  //setup compression algorithm

  PointCloudDecoder = new pcl::io::OctreePointCloudCompression<pcl::PointXYZRGBA> ();
  //\\



  // Create a ROS subscriber for the input point cloud
  ros::Subscriber sub = nh.subscribe ("velodyne_points/compressed", 1, cloud_cb);

  // Create a ROS publisher for the output point cloud
  pub = nh.advertise<sensor_msgs::PointCloud2> ("decompress", 1);

  // Spin
  ros::spin ();

  //delete(PointCloudDecoder);
}

Answer 1

看起来您正在正确使用/调用 pcl 函数。我有我的怀疑。 decodePointCloud 调用的唯一可能引发错误分配的函数（除非我错过了什么）是 vector::reserve。所以，我怀疑你的内存不足。对于非 ros 分配/使用，请参阅其他 SO 帖子 (ex)。至于同节点vs不同节点，这是一个节点和一个nodelet之间的精确区别：

Nodelet 旨在提供一种在单台机器上、在单个进程中运行多种算法的方法，而在进程内传递消息时不会产生复制成本。 roscpp 进行了优化，可以在同一节点内的发布和订阅调用之间进行零复制指针传递。为此，nodelet 允许将类动态加载到同一个节点中，但是它们提供了简单的单独命名空间，因此 nodelet 就像一个单独的节点一样，尽管处于同一个进程中。这已进一步扩展，因为它可以在运行时使用 pluginlib 动态加载。

另见this answer。