我有一个PMD camboard nano，我正在使用this ROS interface将数据发布到ROS网络。 nodelet中的发布者是
ros::Publisher points_publisher_ = nh.advertise<sensor_msgs::PointCloud2>("points_unrectified", 1);
从函数PMDCamboardNano::getPointCloud()检索数据，该函数返回sensor_msgs::PointCloud2Ptr。
在我遇到问题之前，我必须提到节点（和nodelet分别）生成的数据是有效的，我可以在没有RViz内部问题的情况下查看它。
问题：当我使用我的订阅者时，我遇到了分段错误：
#include <ros/ros.h>
#include <pcl/io/io.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
//#include <pcl_ros/publisher.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/filters/statistical_outlier_removal.h>
#include <ros/publisher.h>
#include <string>
class CloudSubscriber
{
protected:
ros::NodeHandle nh;
ros::Subscriber sub;
private:
sensor_msgs::PointCloud2 cloud;
public:
CloudSubscriber()
{
sub = nh.subscribe<sensor_msgs::PointCloud2>("/camera/points_unrectified", 5, &CloudSubscriber::subCallback, this);
}
~CloudSubscriber()
{
sub.shutdown();
}
void subCallback(const sensor_msgs::PointCloud2ConstPtr& msg)
{
if(msg->data.empty())
{
ROS_WARN("Received an empty cloud message. Skipping further processing");
return;
}
ROS_INFO_STREAM("Received a cloud message with " << msg->height * msg->width << " points");
ROS_INFO("Converting ROS cloud message to PCL compatible data structure");
pcl::PointCloud<pcl::PointXYZ> pclCloud;
pcl::fromROSMsg(*msg, pclCloud);
pcl::PointCloud<pcl::PointXYZ>::Ptr p(new pcl::PointCloud<pcl::PointXYZ>(pclCloud));
pcl::PointCloud<pcl::PointXYZ>::Ptr pclCloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);
pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor; // PROBLEM!!!
sor.setInputCloud(p);
sor.setMeanK(50);
sor.setStddevMulThresh(1.0);
ROS_INFO("Filtering cloud data");
// Remove the outliers
sor.filter(*pclCloud_filtered);
ROS_INFO_STREAM("Filtering completed. a cloud message with " << (msg->height*msg->width - pclCloud_filtered->height*pclCloud_filtered->width) << " points as outliers leaving " << pclCloud_filtered->height * pclCloud_filtered->width << " in total");
// Do something with the filtered PCL cloud
//pcl::io::savePCDFileBinaryCompressed("inliers.pcd", *pclCloud_filtered);
}
};
int main(int argc, char* argv[])
{
ros::init (argc, argv, "cloud_subscriber");
ros::NodeHandle nh;
CloudSubscriber c;
while(nh.ok())
ros::spin();
return 0;
}
我在我声明我的统计异常值移除器的位置出现了分段错误。我不知道是什么导致了它。我认为这个问题不在声明本身，而是在某个更深处但我无法弄清楚在哪里。我甚至无法进行调试，因为即使在我将Qt Creator连接到运行节点的外部运行进程之前，节点也会立即崩溃（上帝，我讨厌ROS节点的调试有多复杂!!!）。在我的订阅者被宣布之前添加睡眠也无济于事。
这是another code from my repository on GitHub。唯一的区别是我使用 pcl_ros命名空间中的发布者而不是 ros 命名空间中的发布者来读取文件（而不是设备），最后我将我的PCL云数据直接转换为PointCloud2对象而不是PointCloud2Ptr。这仍然无法解释为什么分段错误发生在那个确切的定义上。
这是我项目的CMakeLists.txt：
cmake_minimum_required(VERSION 2.8.3)
project(pmd_camboard_nano)
set(CMAKE_CXX_FLAGS "--std=gnu++11 ${CMAKE_CXX_FLAGS}")
find_package(catkin REQUIRED COMPONENTS roscpp sensor_msgs image_transport nodelet dynamic_reconfigure tf)
generate_dynamic_reconfigure_options(cfg/PMD.cfg)
catkin_package(
INCLUDE_DIRS include
CATKIN_DEPENDS roscpp sensor_msgs image_transport nodelet dynamic_reconfigure tf pcl_conversions pcl_msgs pcl_ros
DEPENDS boost_system PCL
)
# Set PMDSDK Requirements
set(PMDSDK_ROOT_DIR ${PROJECT_SOURCE_DIR}/PMDSDK) # Change this if the path is different
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${PROJECT_SOURCE_DIR}/cmake/Modules/")
# Register PMDSDK
find_package(PMDSDK REQUIRED)
# Register Boost
find_package(Boost REQUIRED COMPONENTS system)
# Register PCL
find_package(PCL REQUIRED COMPONENTS common io filters)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
#########
# BUILD #
#########
add_definitions(-DPMD_PLUGIN_DIR="${PMDSDK_PLUGIN_DIR}/")
include_directories(include ${catkin_INCLUDE_DIRS} ${PMDSDK_INCLUDE_DIR} ${Boost_INCLUDE_DIRS} ${PCL_INCLUDE_DIRS})
# make sure configure headers are built before any node using them
#set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR})
message(${CATKIN_DEVEL_PREFIX})
add_library(${PROJECT_NAME}_nodelet src/driver_nodelet.cpp src/pmd_camboard_nano.cpp)
target_link_libraries(${PROJECT_NAME}_nodelet ${catkin_LIBRARIES} ${PMDSDK_LIBRARIES})
add_dependencies(${PROJECT_NAME}_nodelet ${PROJECT_NAME}_gencfg)
add_executable(${PROJECT_NAME}_node src/driver_node)
target_link_libraries(${PROJECT_NAME}_node ${catkin_LIBRARIES} ${PMDSDK_LIBRARIES})
add_dependencies(${PROJECT_NAME}_node ${PROJECT_NAME}_gencfg)
add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS})
# The cloud handler receives point clouds either directly from the PMD publishing node (directly controlling
# the PMD device) or from the cloud relay. Once a point cloud message is received, it is further processed
add_executable(${PROJECT_NAME}_cloud_handler src/pmd_camboard_nano_cloud_handler)
target_link_libraries(${PROJECT_NAME}_cloud_handler ${catkin_LIBRARIES} boost_system pthread pcl_common pcl_io pcl_filters)
# TODO
# The cloud relay receives the output from the cloud publishing node (directly controlling the PMD device)
# and re-publish it ONLY when the user triggers it. This is basically used to reduce the amount of data
# and also to regulate which point clouds are passed onto the cloud handler
#add_executable(${PROJECT_NAME}_cloud_relay src/pmd_camboard_nano_cloud_relay)
#target_link_libraries(${PROJECT_NAME}_cloud_relay ${catkin_LIBRARIES} #boost_system pthread pcl_common pcl_io pcl_filters)
修改
啊，Qt Creator实际上可以启动一个外部进程，使用ptrace将其自身挂钩（因为Ubuntu出于安全原因禁止这样的有用的东西，所以启用它）并在main的开头暂停（唯一的问题是我可以只看反汇编LOL）。下面您可以看到在main（）暂停应用程序后的一个步骤：
Function: _ZN5boost4math7lanczos19lanczos_initializerINS1_12lanczos17m64EeE4initC2Ev
0x7f7b4feb6c3c <+0x02cc> rex.B std
0x7f7b4feb6c3e <+0x02ce> (bad)
0x7f7b4feb6c3f <+0x02cf> (bad)
0x7f7b4feb6c40 <+0x02d0> fldt 0x53028a(%rip) # 0x7f7b503e6ed0
0x7f7b4feb6c46 <+0x02d6> mov 0x8dcf0b(%rip),%rax # 0x7f7b50793b58
0x7f7b4feb6c4d <+0x02dd> mov %rbx,%rdi
0x7f7b4feb6c50 <+0x02e0> fstpt (%rax) <------ Qt Creator points here
0x7f7b4feb6c52 <+0x02e2> fldt 0x530288(%rip) # 0x7f7b503e6ee0
0x7f7b4feb6c58 <+0x02e8> fstpt 0x10(%rax)
0x7f7b4feb6c5b <+0x02eb> fldt 0x53028f(%rip) # 0x7f7b503e6ef0
0x7f7b4feb6c61 <+0x02f1> fstpt 0x20(%rax)
0x7f7b4feb6c64 <+0x02f4> fldt 0x530296(%rip) # 0x7f7b503e6f00
0x7f7b4feb6c6a <+0x02fa> fstpt 0x30(%rax)
0x7f7b4feb6c6d <+0x02fd> fldt 0x53029d(%rip) # 0x7f7b503e6f10
0x7f7b4feb6c73 <+0x0303> fstpt 0x40(%rax)
0x7f7b4feb6c76 <+0x0306> fldt 0x5302a4(%rip) # 0x7f7b503e6f20
0x7f7b4feb6c7c <+0x030c> fstpt 0x50(%rax)
0x7f7b4feb6c7f <+0x030f> fldt 0x5302ab(%rip) # 0x7f7b503e6f30
0x7f7b4feb6c85 <+0x0315> fstpt 0x60(%rax)
0x7f7b4feb6c88 <+0x0318> fldt 0x5302b2(%rip) # 0x7f7b503e6f40
0x7f7b4feb6c8e <+0x031e> fstpt 0x70(%rax)
0x7f7b4feb6c91 <+0x0321> fldt 0x5302b9(%rip) # 0x7f7b503e6f50
0x7f7b4feb6c97 <+0x0327> fstpt 0x80(%rax)
0x7f7b4feb6c9d <+0x032d> fldt 0x5302bd(%rip) # 0x7f7b503e6f60
0x7f7b4feb6ca3 <+0x0333> fstpt 0x90(%rax)
0x7f7b4feb6ca9 <+0x0339> fldt 0x5302c1(%rip) # 0x7f7b503e6f70
0x7f7b4feb6caf <+0x033f> fstpt 0xa0(%rax)
似乎一个提升功能正在引起这种情况（据我所知......）：
0 boost::math::lanczos::lanczos_initializer<boost::math::lanczos::lanczos17m64, long double>::init::init() /usr/lib/libpcl_sample_consensus.so.1.7 0x7f7b4feb6c50
1 ?? /usr/lib/libpcl_sample_consensus.so.1.7 0x7f7b4fe8e6de
2 call_init 78 0x7f7b541b413a
3 call_init 36 0x7f7b541b4223
4 _dl_init 126 0x7f7b541b4223
5 _dl_start_user /lib64/ld-linux-x86-64.so.2 0x7f7b541a530a
6 ?? 0x1
7 ?? 0x7ffc39abecce
8 ??
编辑2：越来越近了。以下是有关very similar problem的一些信息。这似乎是PCL 1.7的一个问题。然而，这是ROS Indigo附带的PCL。 ： - /我现在很不高兴......
答案 0 :(得分：0)
Yeap ...除非你用C ++ 11编译了libs，否则PCL 1.7和C ++ 11根本不会发挥出色：
从我的CMakeLists.txt中删除标志后，一切运行顺利。我现在很开心......