ROS上slam_gmapping代码详解

/*
 * slam_gmapping
 * Copyright (c) 2008, Willow Garage, Inc.
 *
 * THE WORK (AS DEFINED BELOW) IS PROVIDED UNDER THE TERMS OF THIS CREATIVE
 * COMMONS PUBLIC LICENSE ("CCPL" OR "LICENSE"). THE WORK IS PROTECTED BY
 * COPYRIGHT AND/OR OTHER APPLICABLE LAW. ANY USE OF THE WORK OTHER THAN AS
 * AUTHORIZED UNDER THIS LICENSE OR COPYRIGHT LAW IS PROHIBITED.
 * 
 * BY EXERCISING ANY RIGHTS TO THE WORK PROVIDED HERE, YOU ACCEPT AND AGREE TO
 * BE BOUND BY THE TERMS OF THIS LICENSE. THE LICENSOR GRANTS YOU THE RIGHTS
 * CONTAINED HERE IN CONSIDERATION OF YOUR ACCEPTANCE OF SUCH TERMS AND
 * CONDITIONS.
 *
 */

/* Author: Brian Gerkey */
/* Modified by: Charles DuHadway */


/**

@mainpage slam_gmapping

@htmlinclude manifest.html

@b slam_gmapping is a wrapper around the GMapping SLAM library. It reads laser
scans and odometry and computes a map. This map can be
written to a file using e.g.

  "rosrun map_server map_saver static_map:=dynamic_map"



@section topic ROS topics

Subscribes to (name/type):
- @b "scan"/sensor_msgs/LaserScan : data from a laser range scanner 
- @b "/tf": odometry from the robot


Publishes to (name/type):
- @b "/tf"/tf/tfMessage: position relative to the map


@section services
 - @b "~dynamic_map" : returns the map


@section parameters ROS parameters

Reads the following parameters from the parameter server

Parameters used by our GMapping wrapper:

- @b "~throttle_scans": @b [int] throw away every nth laser scan
- @b "~base_frame": @b [string] the tf frame_id to use for the robot base pose
- @b "~map_frame": @b [string] the tf frame_id where the robot pose on the map is published
- @b "~odom_frame": @b [string] the tf frame_id from which odometry is read
- @b "~map_update_interval": @b [double] time in seconds between two recalculations of the map


Parameters used by GMapping itself:

Laser Parameters:
- @b "~/maxRange" @b [double] maximum range of the laser scans. Rays beyond this range get discarded completely. (default: maximum laser range minus 1 cm, as received in the the first LaserScan message)
- @b "~/maxUrange" @b [double] maximum range of the laser scanner that is used for map building (default: same as maxRange)
- @b "~/sigma" @b [double] standard deviation for the scan matching process (cell)
- @b "~/kernelSize" @b [int] search window for the scan matching process
- @b "~/lstep" @b [double] initial search step for scan matching (linear)
- @b "~/astep" @b [double] initial search step for scan matching (angular)
- @b "~/iterations" @b [int] number of refinement steps in the scan matching. The final "precision" for the match is lstep*2^(-iterations) or astep*2^(-iterations), respectively.
- @b "~/lsigma" @b [double] standard deviation for the scan matching process (single laser beam)
- @b "~/ogain" @b [double] gain for smoothing the likelihood
- @b "~/lskip" @b [int] take only every (n+1)th laser ray for computing a match (0 = take all rays)
- @b "~/minimumScore" @b [double] minimum score for considering the outcome of the scanmatching good. Can avoid 'jumping' pose estimates in large open spaces when using laser scanners with limited range (e.g. 5m). (0 = default. Scores go up to 600+, try 50 for example when experiencing 'jumping' estimate issues)

Motion Model Parameters (all standard deviations of a gaussian noise model)
- @b "~/srr" @b [double] linear noise component (x and y)
- @b "~/stt" @b [double] angular noise component (theta)
- @b "~/srt" @b [double] linear -> angular noise component
- @b "~/str" @b [double] angular -> linear noise component

Others:
- @b "~/linearUpdate" @b [double] the robot only processes new measurements if the robot has moved at least this many meters
- @b "~/angularUpdate" @b [double] the robot only processes new measurements if the robot has turned at least this many rads

- @b "~/resampleThreshold" @b [double] threshold at which the particles get resampled. Higher means more frequent resampling.
- @b "~/particles" @b [int] (fixed) number of particles. Each particle represents a possible trajectory that the robot has traveled

Likelihood sampling (used in scan matching)
- @b "~/llsamplerange" @b [double] linear range
- @b "~/lasamplerange" @b [double] linear step size
- @b "~/llsamplestep" @b [double] linear range
- @b "~/lasamplestep" @b [double] angular step size

Initial map dimensions and resolution:
- @b "~/xmin" @b [double] minimum x position in the map [m]
- @b "~/ymin" @b [double] minimum y position in the map [m]
- @b "~/xmax" @b [double] maximum x position in the map [m]
- @b "~/ymax" @b [double] maximum y position in the map [m]
- @b "~/delta" @b [double] size of one pixel [m]

*/



#include "slam_gmapping.h"

#include 

#include 

#include "ros/ros.h"
#include "ros/console.h"
#include "nav_msgs/MapMetaData.h"

#include "gmapping/sensor/sensor_range/rangesensor.h"
#include "gmapping/sensor/sensor_odometry/odometrysensor.h"

#include 
#include 
#include 
#define foreach BOOST_FOREACH

// compute linear index for given map coords
#define MAP_IDX(sx, i, j) ((sx) * (j) + (i))

SlamGMapping::SlamGMapping():
  map_to_odom_(tf::Transform(tf::createQuaternionFromRPY( 0, 0, 0 ), tf::Point(0, 0, 0 ))),
  laser_count_(0), private_nh_("~"), scan_filter_sub_(NULL), scan_filter_(NULL), transform_thread_(NULL)
{
  seed_ = time(NULL);
  init();
}

SlamGMapping::SlamGMapping(ros::NodeHandle& nh, ros::NodeHandle& pnh):
  map_to_odom_(tf::Transform(tf::createQuaternionFromRPY( 0, 0, 0 ), tf::Point(0, 0, 0 ))),
  laser_count_(0),node_(nh), private_nh_(pnh), scan_filter_sub_(NULL), scan_filter_(NULL), transform_thread_(NULL)
{
  seed_ = time(NULL);
  init();
}

SlamGMapping::SlamGMapping(long unsigned int seed, long unsigned int max_duration_buffer):
  map_to_odom_(tf::Transform(tf::createQuaternionFromRPY( 0, 0, 0 ), tf::Point(0, 0, 0 ))),
  laser_count_(0) ,//激光雷达计数
 private_nh_("~"), //私有的句柄
scan_filter_sub_(NULL),//激光雷达订阅
 scan_filter_(NULL), //激光雷达滤波器
transform_thread_(NULL),//变换的线程，
  seed_(seed), tf_(ros::Duration(max_duration_buffer))
{
  init();
}


void SlamGMapping::init()
{
  // log4cxx::Logger::getLogger(ROSCONSOLE_DEFAULT_NAME)->setLevel(ros::console::g_level_lookup[ros::console::levels::Debug]);

  // The library is pretty chatty
  //gsp_ = new GMapping::GridSlamProcessor(std::cerr);
  gsp_ = new GMapping::GridSlamProcessor();
  ROS_ASSERT(gsp_);
//gmapping这个命名空间是在basic GridFastSLAM算法的基础上，每个粒子都有其自己的地图和机器人的位姿。

  tfB_ = new tf::TransformBroadcaster();
  ROS_ASSERT(tfB_);

  gsp_laser_ = NULL;
  gsp_odom_ = NULL;

  got_first_scan_ = false;
  got_map_ = false;
//让其里程计的数据为NULL，空指针 
  

  
  // Parameters used by our GMapping wrapper
  if(!private_nh_.getParam("throttle_scans", throttle_scans_))
    throttle_scans_ = 1;
  if(!private_nh_.getParam("base_frame", base_frame_))
    base_frame_ = "base_link";
  if(!private_nh_.getParam("map_frame", map_frame_))
    map_frame_ = "map";
  if(!private_nh_.getParam("odom_frame", odom_frame_))
    odom_frame_ = "odom";
//throttle_scans表示处理的容忍度吧，最小的容忍度。如果设置很高，就会漏掉更多的点
//设置参数的名字，数字和string类型，都可以，然后对这个参数进行设置 

  private_nh_.param("transform_publish_period", transform_publish_period_, 0.05);

  double tmp;
  if(!private_nh_.getParam("map_update_interval", tmp))
    tmp = 5.0;
  map_update_interval_.fromSec(tmp);
  
  // Parameters used by GMapping itself
  maxUrange_ = 0.0;  maxRange_ = 0.0; // preliminary default, will be set in initMapper()
  if(!private_nh_.getParam("minimumScore", minimum_score_))
    minimum_score_ = 0;//每束激光雷达扫描的可能性
  if(!private_nh_.getParam("sigma", sigma_))
    sigma_ = 0.05;//用于暴力匹配 
  if(!private_nh_.getParam("kernelSize", kernelSize_))
    kernelSize_ = 1;//寻找关联的 
  if(!private_nh_.getParam("lstep", lstep_))
    lstep_ = 0.05;//平移优化的步长 
  if(!private_nh_.getParam("astep", astep_))
    astep_ = 0.05;//旋转优化的步长
  if(!private_nh_.getParam("iterations", iterations_))
    iterations_ = 5;//旋转优化的步长 
  if(!private_nh_.getParam("lsigma", lsigma_))
    lsigma_ = 0.075;//平移优化的步长 
  if(!private_nh_.getParam("ogain", ogain_))
    ogain_ = 3.0;//为了重新采样而评估的增益
  if(!private_nh_.getParam("lskip", lskip_))
    lskip_ = 0;//每束激光雷达跳过的激光束 
  if(!private_nh_.getParam("srr", srr_))
    srr_ = 0.1;//srr里程计的平移的/平移 
  if(!private_nh_.getParam("srt", srt_))
    srt_ = 0.2;//srt里程计的平移/旋转 
  if(!private_nh_.getParam("str", str_))
    str_ = 0.1;//stt里程计的旋转/旋转 
  if(!private_nh_.getParam("stt", stt_))
    stt_ = 0.2;//str里程计的旋转/平移 
  if(!private_nh_.getParam("linearUpdate", linearUpdate_))
    linearUpdate_ = 1.0;
  if(!private_nh_.getParam("angularUpdate", angularUpdate_))
    angularUpdate_ = 0.5;
  if(!private_nh_.getParam("temporalUpdate", temporalUpdate_))
    temporalUpdate_ = -1.0;
  if(!private_nh_.getParam("resampleThreshold", resampleThreshold_))
    resampleThreshold_ = 0.5;
  if(!private_nh_.getParam("particles", particles_))
    particles_ = 30;
  if(!private_nh_.getParam("xmin", xmin_))
    xmin_ = -100.0;
  if(!private_nh_.getParam("ymin", ymin_))
    ymin_ = -100.0;
  if(!private_nh_.getParam("xmax", xmax_))
    xmax_ = 100.0;
  if(!private_nh_.getParam("ymax", ymax_))
    ymax_ = 100.0;
  if(!private_nh_.getParam("delta", delta_))
    delta_ = 0.05;
  if(!private_nh_.getParam("occ_thresh", occ_thresh_))
    occ_thresh_ = 0.25;
  if(!private_nh_.getParam("llsamplerange", llsamplerange_))
    llsamplerange_ = 0.01;
  if(!private_nh_.getParam("llsamplestep", llsamplestep_))
    llsamplestep_ = 0.01;
  if(!private_nh_.getParam("lasamplerange", lasamplerange_))
    lasamplerange_ = 0.005;
  if(!private_nh_.getParam("lasamplestep", lasamplestep_))
    lasamplestep_ = 0.005;
    
  if(!private_nh_.getParam("tf_delay", tf_delay_))
    tf_delay_ = transform_publish_period_;

}


void SlamGMapping::startLiveSlam()      //从主函数进入此函数   开始的初始函数
{
  entropy_publisher_ = private_nh_.advertise("entropy", 1, true);//机器人姿态分布的熵的估计值（较高的值表示较大的不确定性）。
  sst_ = node_.advertise("map", 1, true);
  sstm_ = node_.advertise("map_metadata", 1, true);
  ss_ = node_.advertiseService("dynamic_map", &SlamGMapping::mapCallback, this);
  //这三个参数依次是 话题的名称，队列的长度，和是否发布消息
  scan_filter_sub_ = new message_filters::Subscriber(node_, "scan", 5);//订阅的话题
  scan_filter_ = new tf::MessageFilter(*scan_filter_sub_, tf_, odom_frame_, 5);
//   赋值
  scan_filter_->registerCallback(boost::bind(&SlamGMapping::laserCallback, this, _1));
//从这里进入同一个文件的laserCallback函数
  transform_thread_ = new boost::thread(boost::bind(&SlamGMapping::publishLoop, this, transform_publish_period_));
  //开始一个线程
}

void SlamGMapping::startReplay(const std::string & bag_fname, std::string scan_topic)
{
  double transform_publish_period;
  ros::NodeHandle private_nh_("~");
  entropy_publisher_ = private_nh_.advertise("entropy", 1, true);
  sst_ = node_.advertise("map", 1, true);
  sstm_ = node_.advertise("map_metadata", 1, true);
  ss_ = node_.advertiseService("dynamic_map", &SlamGMapping::mapCallback, this);
  
  rosbag::Bag bag;
  bag.open(bag_fname, rosbag::bagmode::Read);
  
  std::vector topics;
  topics.push_back(std::string("/tf"));
  topics.push_back(scan_topic);
  rosbag::View viewall(bag, rosbag::TopicQuery(topics));

  // Store up to 5 messages and there error message (if they cannot be processed right away)
  std::queue > s_queue;
  foreach(rosbag::MessageInstance const m, viewall)
  {
    tf::tfMessage::ConstPtr cur_tf = m.instantiate();
    if (cur_tf != NULL) {
      for (size_t i = 0; i < cur_tf->transforms.size(); ++i)
      {
        geometry_msgs::TransformStamped transformStamped;
        tf::StampedTransform stampedTf;
        transformStamped = cur_tf->transforms[i];
        tf::transformStampedMsgToTF(transformStamped, stampedTf);
        tf_.setTransform(stampedTf);
      }
    }

    sensor_msgs::LaserScan::ConstPtr s = m.instantiate();
    if (s != NULL) {
      if (!(ros::Time(s->header.stamp)).is_zero())
      {
        s_queue.push(std::make_pair(s, ""));
      }
      // Just like in live processing, only process the latest 5 scans
      if (s_queue.size() > 5) {
        ROS_WARN_STREAM("Dropping old scan: " << s_queue.front().second);
        s_queue.pop();
      }
      // ignoring un-timestamped tf data 
    }

    // Only process a scan if it has tf data
    while (!s_queue.empty())
    {
      try
      {
        tf::StampedTransform t;
        tf_.lookupTransform(s_queue.front().first->header.frame_id, odom_frame_, s_queue.front().first->header.stamp, t);
        this->laserCallback(s_queue.front().first);
        s_queue.pop();
      }
      // If tf does not have the data yet
      catch(tf2::TransformException& e)
      {
        // Store the error to display it if we cannot process the data after some time
        s_queue.front().second = std::string(e.what());
        break;
      }
    }
  }

  bag.close();
}

void SlamGMapping::publishLoop(double transform_publish_period){
  if(transform_publish_period == 0)
    return;

  ros::Rate r(1.0 / transform_publish_period);
  while(ros::ok()){
    publishTransform();
    r.sleep();
  }
}

SlamGMapping::~SlamGMapping()//析构函数
{
  if(transform_thread_){
    transform_thread_->join();
    delete transform_thread_;
  }

  delete gsp_;
  if(gsp_laser_)
    delete gsp_laser_;
  if(gsp_odom_)
    delete gsp_odom_;
  if (scan_filter_)
    delete scan_filter_;
  if (scan_filter_sub_)
    delete scan_filter_sub_;
}

bool
SlamGMapping::getOdomPose(GMapping::OrientedPoint& gmap_pose, const ros::Time& t)
{
  // Get the pose of the centered laser at the right time
  centered_laser_pose_.stamp_ = t;
  // Get the laser's pose that is centered
  tf::Stamped odom_pose;
  try
  {
    tf_.transformPose(odom_frame_, centered_laser_pose_, odom_pose);
  }
  catch(tf::TransformException e)
  {
    ROS_WARN("Failed to compute odom pose, skipping scan (%s)", e.what());
    return false;
  }
  double yaw = tf::getYaw(odom_pose.getRotation());

  gmap_pose = GMapping::OrientedPoint(odom_pose.getOrigin().x(),
                                      odom_pose.getOrigin().y(),
                                      yaw);laser_count_++; 
  return true;
}

bool
SlamGMapping::initMapper(const sensor_msgs::LaserScan& scan)
{
  laser_frame_ = scan.header.frame_id;
  // Get the laser's pose, relative to base.
  tf::Stamped ident; //设置单位矩阵
  tf::Stamped laser_pose;  //这是他的激光雷达的位姿
  ident.setIdentity();//设置单位矩阵
  ident.frame_id_ = laser_frame_;//这是frameid
  ident.stamp_ = scan.header.stamp;//这是ID
  try//这里用来抛出一个异常，其实就是查看着两个TF之间的关系
  {
    tf_.transformPose(base_frame_, ident, laser_pose);//两个TF之间的关系
  }
  catch(tf::TransformException e)//这里输出一个e
  {
    ROS_WARN("Failed to compute laser pose, aborting initialization (%s)",
             e.what());
    return false;
  }
  //创造一个点在激光雷达laser_pose是他的位姿。然后就是在原点
  // create a point 1m above the laser position and transform it into the laser-frame
  tf::Vector3 v;//其实激光雷达的位姿，然后
  v.setValue(0, 0, 1 + laser_pose.getOrigin().z());
  tf::Stamped up(v, scan.header.stamp,
                                      base_frame_);
  try
  {
    tf_.transformPoint(laser_frame_, up, up);
    ROS_DEBUG("Z-Axis in sensor frame: %.3f", up.z());
  }
  catch(tf::TransformException& e)
  {
    ROS_WARN("Unable to determine orientation of laser: %s",//这里就是抛出一个异常
             e.what());
    return false;
  }
  
  // gmapping doesnt take roll or pitch into account. So check for correct sensor alignment.
  if (fabs(fabs(up.z()) - 1) > 0.001)
  {
    ROS_WARN("Laser has to be mounted planar! Z-coordinate has to be 1 or -1, but gave: %.5f",
                 up.z());
    return false;
  }

  gsp_laser_beam_count_ = scan.ranges.size();//对gmapping 进行计算数值

  double angle_center = (scan.angle_min + scan.angle_max)/2;//得到中间的角度值。

  if (up.z() > 0)
  {
    do_reverse_range_ = scan.angle_min > scan.angle_max;
    centered_laser_pose_ = tf::Stamped(tf::Transform(tf::createQuaternionFromRPY(0,0,angle_center),
                            -                                   tf::Vector3(0,0,0)), ros::Time::now(), laser_frame_);
    ROS_INFO("Laser is mounted upwards.");
  }
  else
  {
    do_reverse_range_ = scan.angle_min < scan.angle_max;  //如果最小的值比最大的值大的话，那么返回一个bool值
    centered_laser_pose_ = tf::Stamped(tf::Transform(tf::createQuaternionFromRPY(M_PI,0,-angle_center),
                                                               tf::Vector3(0,0,0)), ros::Time::now(), laser_frame_);
    ROS_INFO("Laser is mounted upside down.");
  }

  // Compute the angles of the laser from -x to x, basically symmetric and in increasing order
  laser_angles_.resize(scan.ranges.size());
  // Make sure angles are started so that they are centered
  double theta = - std::fabs(scan.angle_min - scan.angle_max)/2;
  for(unsigned int i=0; igetName(), gsp_laser_));
  gsp_->setSensorMap(smap);

  gsp_odom_ = new GMapping::OdometrySensor(odom_frame_);
  ROS_ASSERT(gsp_odom_);


  /// @todo Expose setting an initial pose
  GMapping::OrientedPoint initialPose;
  if(!getOdomPose(initialPose, scan.header.stamp))
  {
    ROS_WARN("Unable to determine inital pose of laser! Starting point will be set to zero.");
    initialPose = GMapping::OrientedPoint(0.0, 0.0, 0.0);
  }

  gsp_->setMatchingParameters(maxUrange_, maxRange_, sigma_,
                              kernelSize_, lstep_, astep_, iterations_,
                              lsigma_, ogain_, lskip_);

  gsp_->setMotionModelParameters(srr_, srt_, str_, stt_);
  gsp_->setUpdateDistances(linearUpdate_, angularUpdate_, resampleThreshold_);
  gsp_->setUpdatePeriod(temporalUpdate_);
  gsp_->setgenerateMap(false);
  gsp_->GridSlamProcessor::init(particles_, xmin_, ymin_, xmax_, ymax_,
                                delta_, initialPose);
  gsp_->setllsamplerange(llsamplerange_);
  gsp_->setllsamplestep(llsamplestep_);
  /// @todo Check these calls; in the gmapping gui, they use
  /// llsamplestep and llsamplerange intead of lasamplestep and
  /// lasamplerange.  It was probably a typo, but who knows.
  gsp_->setlasamplerange(lasamplerange_);
  gsp_->setlasamplestep(lasamplestep_);
  gsp_->setminimumScore(minimum_score_);

  // Call the sampling function once to set the seed.
  GMapping::sampleGaussian(1,seed_);

  ROS_INFO("Initialization complete");

  return true;
}

bool
SlamGMapping::addScan(const sensor_msgs::LaserScan& scan, GMapping::OrientedPoint& gmap_pose)
{
  if(!getOdomPose(gmap_pose, scan.header.stamp))
     return false;
  
  if(scan.ranges.size() != gsp_laser_beam_count_)
    return false;

  // GMapping wants an array of doubles...
  double* ranges_double = new double[scan.ranges.size()];
  // If the angle increment is negative, we have to invert the order of the readings.
  if (do_reverse_range_)
  {
    ROS_DEBUG("Inverting scan");
    int num_ranges = scan.ranges.size();
    for(int i=0; i < num_ranges; i++)     // 把小于扫描最短范围的数据滤出 
    {
      // Must filter out short readings, because the mapper won't
      if(scan.ranges[num_ranges - i - 1] < scan.range_min)
        ranges_double[i] = (double)scan.range_max;
      else
        ranges_double[i] = (double)scan.ranges[num_ranges - i - 1];
    }
  } else 
  {
    for(unsigned int i=0; i < scan.ranges.size(); i++)
    {
      // Must filter out short readings, because the mapper won't
      if(scan.ranges[i] < scan.range_min)
        ranges_double[i] = (double)scan.range_max;
      else
        ranges_double[i] = (double)scan.ranges[i];
    }
  }

  GMapping::RangeReading reading(scan.ranges.size(),
                                 ranges_double,
                                 gsp_laser_,
                                 scan.header.stamp.toSec());

  // ...but it deep copies them in RangeReading constructor, so we don't
  // need to keep our array around.
  delete[] ranges_double;

  reading.setPose(gmap_pose);

  /*
  ROS_DEBUG("scanpose (%.3f): %.3f %.3f %.3f\n",
            scan.header.stamp.toSec(),
            gmap_pose.x,
            gmap_pose.y,
            gmap_pose.theta);
            */
  ROS_DEBUG("processing scan");

  return gsp_->processScan(reading);      // 从这里进入particle filter   
}

void
SlamGMapping::laserCallback(const sensor_msgs::LaserScan::ConstPtr& scan)
{
  laser_count_++;
  if ((laser_count_ % throttle_scans_) != 0)
    return;

  static ros::Time last_map_update(0,0);   //静态变量

  // We can't initialize the mapper until we've got the first scan
  if(!got_first_scan_)
  {
    if(!initMapper(*scan))// 进入initMapper 函数  为bool类型函数
      return;
    got_first_scan_ = true;
  }

  GMapping::OrientedPoint odom_pose;

  if(addScan(*scan, odom_pose))  // 进入addScan函数
  {
    ROS_DEBUG("scan processed");

    GMapping::OrientedPoint mpose = gsp_->getParticles()[gsp_->getBestParticleIndex()].pose;
    ROS_DEBUG("new best pose: %.3f %.3f %.3f", mpose.x, mpose.y, mpose.theta);
    ROS_DEBUG("odom pose: %.3f %.3f %.3f", odom_pose.x, odom_pose.y, odom_pose.theta);
    ROS_DEBUG("correction: %.3f %.3f %.3f", mpose.x - odom_pose.x, mpose.y - odom_pose.y, mpose.theta - odom_pose.theta);

    tf::Transform laser_to_map = tf::Transform(tf::createQuaternionFromRPY(0, 0, mpose.theta), tf::Vector3(mpose.x, mpose.y, 0.0)).inverse();
    tf::Transform odom_to_laser = tf::Transform(tf::createQuaternionFromRPY(0, 0, odom_pose.theta), tf::Vector3(odom_pose.x, odom_pose.y, 0.0));

    map_to_odom_mutex_.lock();
    map_to_odom_ = (odom_to_laser * laser_to_map).inverse();
    map_to_odom_mutex_.unlock();

    if(!got_map_ || (scan->header.stamp - last_map_update) > map_update_interval_)
    {
      updateMap(*scan);
      last_map_update = scan->header.stamp;
      ROS_DEBUG("Updated the map");
    }
  } else
    ROS_DEBUG("cannot process scan");
}

double
SlamGMapping::computePoseEntropy()
{
  double weight_total=0.0;
  for(std::vector::const_iterator it = gsp_->getParticles().begin();
      it != gsp_->getParticles().end();
      ++it)
  {
    weight_total += it->weight;
  }
  double entropy = 0.0;
  for(std::vector::const_iterator it = gsp_->getParticles().begin();
      it != gsp_->getParticles().end();
      ++it)
  {
    if(it->weight/weight_total > 0.0)
      entropy += it->weight/weight_total * log(it->weight/weight_total);
  }
  return -entropy;
}

void
SlamGMapping::updateMap(const sensor_msgs::LaserScan& scan)
{
  ROS_DEBUG("Update map");
  boost::mutex::scoped_lock map_lock (map_mutex_);
  GMapping::ScanMatcher matcher;

  matcher.setLaserParameters(scan.ranges.size(), &(laser_angles_[0]),
                             gsp_laser_->getPose());

  matcher.setlaserMaxRange(maxRange_);
  matcher.setusableRange(maxUrange_);
  matcher.setgenerateMap(true);
  /* 取最优粒子，根据权重和weightSum 判断（最大） */
  GMapping::GridSlamProcessor::Particle best =
          gsp_->getParticles()[gsp_->getBestParticleIndex()];
  std_msgs::Float64 entropy;
  entropy.data = computePoseEntropy();
  if(entropy.data > 0.0)
    entropy_publisher_.publish(entropy);

  if(!got_map_) {
    map_.map.info.resolution = delta_;
    map_.map.info.origin.position.x = 0.0;
    map_.map.info.origin.position.y = 0.0;
    map_.map.info.origin.position.z = 0.0;
    map_.map.info.origin.orientation.x = 0.0;
    map_.map.info.origin.orientation.y = 0.0;
    map_.map.info.origin.orientation.z = 0.0;
    map_.map.info.origin.orientation.w = 1.0;
  } 

  GMapping::Point center;
  center.x=(xmin_ + xmax_) / 2.0;
  center.y=(ymin_ + ymax_) / 2.0;

  GMapping::ScanMatcherMap smap(center, xmin_, ymin_, xmax_, ymax_, 
                                delta_);
  /*得到机器人最优轨迹 */
  ROS_DEBUG("Trajectory tree:");
  for(GMapping::GridSlamProcessor::TNode* n = best.node;
      n;
      n = n->parent)
  {
    ROS_DEBUG("  %.3f %.3f %.3f",
              n->pose.x,
              n->pose.y,
              n->pose.theta);
    if(!n->reading)
    {
      ROS_DEBUG("Reading is NULL");
      continue;
    }
	/*重新计算栅格单元的概率*/
    matcher.invalidateActiveArea();
    matcher.computeActiveArea(smap, n->pose, &((*n->reading)[0]));
    matcher.registerScan(smap, n->pose, &((*n->reading)[0]));
  }

  // the map may have expanded, so resize ros message as well
  if(map_.map.info.width != (unsigned int) smap.getMapSizeX() || map_.map.info.height != (unsigned int) smap.getMapSizeY()) {

    // NOTE: The results of ScanMatcherMap::getSize() are different from the parameters given to the constructor
    //       so we must obtain the bounding box in a different way
    GMapping::Point wmin = smap.map2world(GMapping::IntPoint(0, 0));
    GMapping::Point wmax = smap.map2world(GMapping::IntPoint(smap.getMapSizeX(), smap.getMapSizeY()));
    xmin_ = wmin.x; ymin_ = wmin.y;
    xmax_ = wmax.x; ymax_ = wmax.y;
    
    ROS_DEBUG("map size is now %dx%d pixels (%f,%f)-(%f, %f)", smap.getMapSizeX(), smap.getMapSizeY(),
              xmin_, ymin_, xmax_, ymax_);

    map_.map.info.width = smap.getMapSizeX();
    map_.map.info.height = smap.getMapSizeY();
    map_.map.info.origin.position.x = xmin_;
    map_.map.info.origin.position.y = ymin_;
    map_.map.data.resize(map_.map.info.width * map_.map.info.height);//地图需要膨胀

    ROS_DEBUG("map origin: (%f, %f)", map_.map.info.origin.position.x, map_.map.info.origin.position.y);
  }
  /*确定地图的未知区域、自由区域、障碍 */
  for(int x=0; x < smap.getMapSizeX(); x++)
  {
    for(int y=0; y < smap.getMapSizeY(); y++)
    {
      /// @todo Sort out the unknown vs. free vs. obstacle thresholding
      GMapping::IntPoint p(x, y);
      double occ=smap.cell(p);
      assert(occ <= 1.0);
      if(occ < 0)
        map_.map.data[MAP_IDX(map_.map.info.width, x, y)] = -1;
      else if(occ > occ_thresh_)
      {
        //map_.map.data[MAP_IDX(map_.map.info.width, x, y)] = (int)round(occ*100.0);
        map_.map.data[MAP_IDX(map_.map.info.width, x, y)] = 100;
      }
      else
        map_.map.data[MAP_IDX(map_.map.info.width, x, y)] = 0;
    }
  }
  got_map_ = true;

  //make sure to set the header information on the map
  map_.map.header.stamp = ros::Time::now();
  map_.map.header.frame_id = tf_.resolve( map_frame_ );

  sst_.publish(map_.map);
  sstm_.publish(map_.map.info);
}

bool 
SlamGMapping::mapCallback(nav_msgs::GetMap::Request  &req,
                          nav_msgs::GetMap::Response &res)
{
  boost::mutex::scoped_lock map_lock (map_mutex_);
  if(got_map_ && map_.map.info.width && map_.map.info.height)
  {
    res = map_;
    return true;
  }
  else
    return false;
}

void SlamGMapping::publishTransform()
{
  map_to_odom_mutex_.lock();
  ros::Time tf_expiration = ros::Time::now() + ros::Duration(tf_delay_);
  tfB_->sendTransform( tf::StampedTransform (map_to_odom_, tf_expiration, map_frame_, odom_frame_));
  map_to_odom_mutex_.unlock();
}