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#ifndef _READ_VELODYNE_CPP_
#define _READ_VELODYNE_CPP_

#include "read_velodyne.h"

class c_polygon_representation
{
  public:

    c_polygon_representation()
    {
     coefficients =  pcl::ModelCoefficients::Ptr(new pcl::ModelCoefficients);
     indices = pcl::PointIndices::Ptr(new pcl::PointIndices); 
    
    }

    ~c_polygon_representation()
    {
     delete &coefficients;
     delete &indices;
    }


    pcl::ModelCoefficients::Ptr coefficients;
    pcl::PointIndices::Ptr indices;
    pcl::PointCloud<PointT> cloud;



  private:



};

void signal_handler(int sig)
{
        printf("%d %d %d\n",sig,SIGSEGV,SIGINT);
        
        if(sig==SIGSEGV)
        {       
        
                signal(SIGSEGV, SIG_DFL); 
        
                ROS_WARN("System segfaulted"); 
        
                ros::shutdown();
        
                exit(0);
        }
        else if(sig==SIGINT)
        {
                ROS_WARN("Ctrl-c pressed"); 
        
                ros::shutdown();
        
                exit(0);
        }
}


int main(int argc, char **argv)
{
         if(argc < 4) {
        fprintf(stderr, 
                "usage: example4-velodyne <logfile> <start_time> <end time>\n"
                "\n"
                "start_time and end_time are given in seconds from the\n"
                "start of the log file\n");
        return 1;
    }

    lcm_eventlog_t *log = lcm_eventlog_create(argv[1], "r");
    if(!log) {
        fprintf(stderr, "error opening log file\n");
        return 1;
    }

    double start_time = strtod(argv[2], NULL);
    double end_time = strtod(argv[3], NULL);

    Config *config = config_parse_default();
    if(!config) {
        fprintf(stderr, "couldn't find config file\n");
        return 1;
    }

    // load the velodyne sensor calibration
    velodyne_calib_t *vcalib = velodyne_calib_create();

    // read the first timestamp of the log file
    lcm_eventlog_event_t *event = lcm_eventlog_read_next_event(log);
    int64_t first_timestamp = event->timestamp;

    // compute the desired start and end timestamps
    int64_t start_utime = first_timestamp + (int64_t)(start_time * 1000000);
    int64_t end_utime = first_timestamp + (int64_t)(end_time * 1000000);

    lcmtypes_pose_t last_pose;
    memset(&last_pose, 0, sizeof(last_pose));


        t_flags.debug=false;

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

  ros::NodeHandle n;
  ros::Publisher cloud_pub = n.advertise<sensor_msgs::PointCloud2>("cloud", 1);

  ros::Publisher pub[10];

  for (int i=0; i< _NUM_POLYGONS_; i ++)
  {
    char str[256];
    sprintf(str, "plg_%d",i);
    pub[i] = n.advertise<sensor_msgs::PointCloud2>(str, 1);
  }

  ros::Publisher marker_pub = n.advertise<visualization_msgs::Marker>("visualization_marker", 10);


  ros::Rate r(0.5);

  //pcl::PointCloud<PointT>::Ptr cloud(new pcl::PointCloud<PointT>);
  pcl::PointCloud<PointT> cloud;
  sensor_msgs::PointCloud2 cloud_msg;
  cloud.header.frame_id = "/sensor_frame";
  cloud.height = 1;
  cloud.is_dense=0;

  while(1)
  {
        // release the last event
        lcm_eventlog_free_event(event);

        // read an event
        event = lcm_eventlog_read_next_event(log);

        if(!event)
            break;

        // always keep track of the current pose
        if(!strcmp(event->channel, "POSE")) {
            if(last_pose.utime) 
                lcmtypes_pose_t_decode_cleanup(&last_pose);

            lcmtypes_pose_t_decode(event->data, 0, event->datalen, &last_pose);
        }

        // ignore other messages until the desired start time
        if(event->timestamp < start_utime) {
            continue;
        }

        // quit if we're done
        if(event->timestamp >= end_utime) {
            break;
        }

        if(!strcmp(event->channel, "VELODYNE")) {
            // parse the LCM packet into a velodyne data packet.
            lcmtypes_velodyne_t vel;
            lcmtypes_velodyne_t_decode(event->data, 0, event->datalen, 
                    &vel);

            // compute the velodyne-to-local transformation matrix
            // 
            // This is an approximation because we're using the last recorded
            // pose.  A more accurate projection might be to project the
            // vehicle's pose forward based on its last measured velocity.
            double velodyne_to_local[16];
            config_util_sensor_to_local_with_pose (config, "VELODYNE", 
                velodyne_to_local, &last_pose);

            // parse the velodyne data packet
            velodyne_decoder_t vdecoder;
            velodyne_decoder_init(vcalib, &vdecoder, vel.data, vel.datalen);

            // project each sample in the velodyne data packet into the local
            // frame
            velodyne_sample_t vsample;

            while (!velodyne_decoder_next(vcalib, &vdecoder, &vsample))
            {
                if (vsample.range < 0.01)
                {
                    continue;
                }

                double sensor_xyz[4] = {vsample.xyz[0], vsample.xyz[1], vsample.xyz[2], 1 };
                double local_xyz[4];

                matrix_vector_multiply_4x4_4d(velodyne_to_local, sensor_xyz, local_xyz);

                //printf("%f %f %f\n", local_xyz[0], local_xyz[1], local_xyz[2]);

   
                PointT Pt;
                Pt.x = local_xyz[0];
                Pt.y = local_xyz[1];
                Pt.z = local_xyz[2];

                //Pt.x = sensor_xyz[0];
                //Pt.y = sensor_xyz[1];
                //Pt.z = sensor_xyz[2];
                cloud.push_back(Pt);
                
            }

            cloud.width = cloud.size();
            lcmtypes_velodyne_t_decode_cleanup(&vel);
        }
}
 
  while(n.ok())
  {

    visualization_msgs::Marker markers;
    markers.header.frame_id = "/sensor_frame";
    markers.header.stamp = ros::Time::now();
    markers.ns = "triangles";
    markers.action = visualization_msgs::Marker::ADD;
    markers.pose.orientation.w = 1.0;
    markers.type = visualization_msgs::Marker::TRIANGLE_LIST;

    markers.scale.x = 1;
    markers.scale.y = 1;
    markers.scale.z = 1;
    
    markers.color.r = 1;
    markers.color.g = 1;
    markers.color.b = 1;
    markers.color.a = 1;

    geometry_msgs::Point p;
    std_msgs::ColorRGBA color;
    p.x = 0;
    p.y = 0;
    p.z = 0;
    markers.points.push_back(p);
    color.r = 1.0f;
    color.g = 0.2f;
    color.b = 1.0f;
    color.a = 1.0;
    markers.colors.push_back(color);

    p.x = 10;
    p.y = 10;
    p.z = 0;
    markers.points.push_back(p);
    color.r = 1.0f;
    color.g = 0.2f;
    color.b = 0.5f;
    color.a = 1.0;
    markers.colors.push_back(color);

    p.x = 10;
    p.y = -10;
    p.z = 0;
    markers.points.push_back(p);
    color.r = 0.8f;
    color.g = 0.2f;
    color.b = 1.0f;
    color.a = 1.0;
    markers.colors.push_back(color);

    marker_pub.publish(markers);

    printf("num pts = %d\n",(int)markers.points.size());
    printf("num colors = %d\n",(int)markers.colors.size());

    cloud.header.stamp = ros::Time::now();
    ROS_INFO("publishing cloud with %d points",(int)cloud.size());

    pcl::toROSMsg(cloud, cloud_msg);
    cloud_pub.publish(cloud_msg);

    c_polygon_representation *plg[10];

    //pcl::ModelCoefficients coefficients;
    //pcl::PointIndices::Ptr indices_model(new pcl::PointIndices);
    //pcl::PointCloud<PointT> cloud_model;
    
    sensor_msgs::PointCloud2 cloud_model_msg;


    pcl::SACSegmentation<PointT> seg;
    seg.setOptimizeCoefficients(true);
    seg.setModelType(pcl::SACMODEL_PLANE);
    seg.setMethodType (pcl::SAC_RANSAC); 
    seg.setDistanceThreshold (0.3);
    seg.setMaxIterations (1000);

    pcl::ExtractIndices<PointT> extract;

    
    pcl::PointCloud<PointT> cloud_tmp;
    cloud_tmp = cloud;

    for (int i=0; i<_NUM_POLYGONS_;i++)
    {

      plg[i] = new c_polygon_representation;
      seg.setInputCloud(cloud_tmp.makeShared());
      seg.segment(*plg[i]->indices, *plg[i]->coefficients);

      if (plg[i]->indices->indices.size () == 0)
      {
        ROS_ERROR("Could not estimate a planar model for the given dataset."); return (-1);
      }
      //std::cerr << "Model coefficients: " << coefficients[i].values[0] << " " << coefficients[i].values[1] << " " << coefficients[i].values[2] << " " coefficients[i].values[3] << std::endl;
      //std::cerr << "Model inliers: " << model[i].size () << std::endl;

      extract.setInputCloud(cloud_tmp.makeShared());
      extract.setIndices(plg[i]->indices);
      extract.setNegative(false);
      extract.filter(plg[i]->cloud);
      extract.setNegative(true);
      extract.filter(cloud_tmp);
        }

    for (int i=0; i<_NUM_POLYGONS_;i++)
    {

      plg[i]->cloud.header.frame_id = "/sensor_frame";
      plg[i]->cloud.height = 1; //1 since its and unordered pc
      plg[i]->cloud.is_dense=0;
      plg[i]->cloud.width = plg[i]->cloud.size();
      ROS_INFO("publishing cloud_model[%d] with %d points",i,(int)plg[i]->cloud.size());
      pcl::toROSMsg(plg[i]->cloud, cloud_model_msg);
      pub[i].publish(cloud_model_msg);
    }










  //for (size_t i = 0; i < inliers.indices.size (); ++i)
  //{
    //Pt.x = cloud.points[inliers.indices[i]].x;
    //Pt.y = cloud.points[inliers.indices[i]].y;
    //Pt.z = cloud.points[inliers.indices[i]].z;

    //uint8_t r = 255, g = 0, b = 0;    // Example: Red color
    //uint32_t rgb = ((uint32_t)r << 16 | (uint32_t)g << 8 | (uint32_t)b);
    //Pt.rgb = *reinterpret_cast<float*>(&rgb);

    //cloud_inliers.push_back(Pt);
  //}

    //cloud_inliers.header.stamp = ros::Time::now();
    //cloud_inliers.width = cloud_inliers.size();
    //ROS_INFO("publishing cloud_inliers with %d points",cloud_inliers.size());
    //pcl::toROSMsg(cloud_inliers, cloud_inliers_msg);
    //cloud_inliers_pub.publish(cloud_inliers_msg);

    //pcl::ExtractIndices<PointXYZ> extract;

    

    r.sleep();


}
     lcm_eventlog_free_event(event);

    lcm_eventlog_destroy(log);
   

         return 0;
}

#endif

---

mit_darpa_logs_player
Author(s): Miguel Oliveira
autogenerated on Wed Jul 23 04:34:16 2014