#include <costmap_2d/obstacle_layer.h>
#include <costmap_2d/costmap_math.h>
#include <costmap_2d/utils.h>
// #include <tf2_ros/message_filter.h>
#include <sensor_msgs/point_cloud2_iterator.h>
#include <tf2/utils.h>
#include <boost/dll/alias.hpp>

using costmap_2d::NO_INFORMATION;
using costmap_2d::LETHAL_OBSTACLE;
using costmap_2d::FREE_SPACE;

using costmap_2d::ObservationBuffer;
using costmap_2d::Observation;

namespace costmap_2d
{

void ObstacleLayer::onInitialize()
{
  getParams();
//   ros::NodeHandle nh("~/" + name_), g_nh;
  rolling_window_ = layered_costmap_->isRolling();
  

  bool track_unknown_space;
//   nh.param("track_unknown_space", track_unknown_space, layered_costmap_->isTrackingUnknown());
  if (track_unknown_space)
    default_value_ = NO_INFORMATION;
  else
    default_value_ = FREE_SPACE;

  ObstacleLayer::matchSize();
  current_ = true;

  global_frame_ = layered_costmap_->getGlobalFrameID();
  double transform_tolerance;
//   nh.param("transform_tolerance", transform_tolerance, 0.2);

  std::string topics_string;
  // get the topics that we'll subscribe to from the parameter server
//   nh.param("observation_sources", topics_string, std::string(""));
//   ROS_INFO("    Subscribed to Topics: %s", topics_string.c_str());

  // now we need to split the topics based on whitespace which we can use a stringstream for
  std::stringstream ss(topics_string);
/*
  std::string source;
  while (ss >> source)
  {
    ros::NodeHandle source_node(nh, source);

    // get the parameters for the specific topic
    double observation_keep_time, expected_update_rate, min_obstacle_height, max_obstacle_height;
    std::string topic, sensor_frame, data_type;
    bool inf_is_valid, clearing, marking;

    source_node.param("topic", topic, source);
    source_node.param("sensor_frame", sensor_frame, std::string(""));
    source_node.param("observation_persistence", observation_keep_time, 0.0);
    source_node.param("expected_update_rate", expected_update_rate, 0.0);
    source_node.param("data_type", data_type, std::string("PointCloud"));
    source_node.param("min_obstacle_height", min_obstacle_height, 0.0);
    source_node.param("max_obstacle_height", max_obstacle_height, 2.0);
    source_node.param("inf_is_valid", inf_is_valid, false);
    source_node.param("clearing", clearing, false);
    source_node.param("marking", marking, true);

    if (!(data_type == "PointCloud2" || data_type == "PointCloud" || data_type == "LaserScan"))
    {
      ROS_FATAL("Only topics that use point clouds or laser scans are currently supported");
      throw std::runtime_error("Only topics that use point clouds or laser scans are currently supported");
    }

    std::string raytrace_range_param_name, obstacle_range_param_name;

    // get the obstacle range for the sensor
    double obstacle_range = 2.5;
    if (source_node.searchParam("obstacle_range", obstacle_range_param_name))
    {
      source_node.getParam(obstacle_range_param_name, obstacle_range);
    }

    // get the raytrace range for the sensor
    double raytrace_range = 3.0;
    if (source_node.searchParam("raytrace_range", raytrace_range_param_name))
    {
      source_node.getParam(raytrace_range_param_name, raytrace_range);
    }

    printf("Creating an observation buffer for source %s, topic %s, frame %s", source.c_str(), topic.c_str(),
              sensor_frame.c_str());

    // create an observation buffer
    observation_buffers_.push_back(
        boost::shared_ptr < ObservationBuffer
            > (new ObservationBuffer(topic, observation_keep_time, expected_update_rate, min_obstacle_height,
                                     max_obstacle_height, obstacle_range, raytrace_range, *tf_, global_frame_,
                                     sensor_frame, transform_tolerance)));

    // check if we'll add this buffer to our marking observation buffers
    if (marking)
      marking_buffers_.push_back(observation_buffers_.back());

    // check if we'll also add this buffer to our clearing observation buffers
    if (clearing)
      clearing_buffers_.push_back(observation_buffers_.back());

    printf(
        "Created an observation buffer for source %s, topic %s, global frame: %s, "
        "expected update rate: %.2f, observation persistence: %.2f",
        source.c_str(), topic.c_str(), global_frame_.c_str(), expected_update_rate, observation_keep_time);

    // create a callback for the topic
    if (data_type == "LaserScan")
    {
      boost::shared_ptr < message_filters::Subscriber<sensor_msgs::LaserScan>
          > sub(new message_filters::Subscriber<sensor_msgs::LaserScan>(g_nh, topic, 50));

      boost::shared_ptr<tf2_ros::MessageFilter<sensor_msgs::LaserScan> > filter(
        new tf2_ros::MessageFilter<sensor_msgs::LaserScan>(*sub, *tf_, global_frame_,50 , g_nh));

      if (inf_is_valid)
      {
        filter->registerCallback([this,buffer=observation_buffers_.back()](auto& msg){ laserScanValidInfCallback(msg, buffer); });
      }
      else
      {
        filter->registerCallback([this,buffer=observation_buffers_.back()](auto& msg){ laserScanCallback(msg, buffer); });
      }

      observation_subscribers_.push_back(sub);
      observation_notifiers_.push_back(filter);

      observation_notifiers_.back()->setTolerance(ros::Duration(0.05));
    }
    else if (data_type == "PointCloud")
    {
      boost::shared_ptr < message_filters::Subscriber<sensor_msgs::PointCloud>
          > sub(new message_filters::Subscriber<sensor_msgs::PointCloud>(g_nh, topic, 50));

      if (inf_is_valid)
      {
       ROS_WARN("obstacle_layer: inf_is_valid option is not applicable to PointCloud observations.");
      }

        boost::shared_ptr < tf2_ros::MessageFilter<sensor_msgs::PointCloud>
        > filter(new tf2_ros::MessageFilter<sensor_msgs::PointCloud>(*sub, *tf_, global_frame_, 50, g_nh));
        filter->registerCallback([this,buffer=observation_buffers_.back()](auto& msg){ pointCloudCallback(msg, buffer); });

      observation_subscribers_.push_back(sub);
      observation_notifiers_.push_back(filter);
    }
    else
    {
      boost::shared_ptr < message_filters::Subscriber<sensor_msgs::PointCloud2>
          > sub(new message_filters::Subscriber<sensor_msgs::PointCloud2>(g_nh, topic, 50));

      if (inf_is_valid)
      {
       ROS_WARN("obstacle_layer: inf_is_valid option is not applicable to PointCloud observations.");
      }

      boost::shared_ptr < tf2_ros::MessageFilter<sensor_msgs::PointCloud2>
      > filter(new tf2_ros::MessageFilter<sensor_msgs::PointCloud2>(*sub, *tf_, global_frame_, 50, g_nh));
      filter->registerCallback([this,buffer=observation_buffers_.back()](auto& msg){ pointCloud2Callback(msg, buffer); });

      observation_subscribers_.push_back(sub);
      observation_notifiers_.push_back(filter);
    }

    if (sensor_frame != "")
    {
      std::vector < std::string > target_frames;
      target_frames.push_back(global_frame_);
      target_frames.push_back(sensor_frame);
      observation_notifiers_.back()->setTargetFrames(target_frames);
    }
  }
*/
//   dsrv_ = NULL;
//   setupDynamicReconfigure(nh);
}

// void ObstacleLayer::setupDynamicReconfigure(ros::NodeHandle& nh)
// {
//   dsrv_ = new dynamic_reconfigure::Server<costmap_2d::ObstaclePluginConfig>(nh);
//   dynamic_reconfigure::Server<costmap_2d::ObstaclePluginConfig>::CallbackType cb =
//       [this](auto& config, auto level){ reconfigureCB(config, level); };
//   dsrv_->setCallback(cb);
// }

ObstacleLayer::~ObstacleLayer()
{}

bool StaticLayer::getParams()
{
    try {
        YAML::Node config = YAML::LoadFile("/home/duongtd/robotics_core/costmap_2d/config/config.yaml");
        YAML::Node layer = config["obstacle_layer"];

        bool enabled = loadParam(layer, "enabled", true);
        bool footprint_clearing_enabled = loadParam(layer, "footprint_clearing_enabled", true);
        double max_obstacle_height = loadParam(layer, "max_obstacle_height", 2);
        int combination_method = loadParam(layer, "combination_method", 1);

        enabled_ = enabled;
        footprint_clearing_enabled_ = footprint_clearing_enabled;
        max_obstacle_height_ = max_obstacle_height;
        combination_method_ = combination_method;
    } 
    catch (const YAML::BadFile& e) {
        std::cerr << "Cannot open YAML file: " << e.what() << std::endl;
        return false;
    }

    return true;
}

// void ObstacleLayer::laserScanCallback(const sensor_msgs::LaserScanConstPtr& message,
//                                       const boost::shared_ptr<ObservationBuffer>& buffer)
// {
//   // project the laser into a point cloud
//   sensor_msgs::PointCloud2 cloud;
//   cloud.header = message->header;

//   // project the scan into a point cloud
//   try
//   {
//     projector_.transformLaserScanToPointCloud(message->header.frame_id, *message, cloud, *tf_);
//   }
//   catch (tf2::TransformException &ex)
//   {
//     ROS_WARN("High fidelity enabled, but TF returned a transform exception to frame %s: %s", global_frame_.c_str(),
//              ex.what());
//     projector_.projectLaser(*message, cloud);
//   }
//   catch (std::runtime_error &ex)
//   {
//     ROS_WARN("transformLaserScanToPointCloud error, it seems the message from laser sensor is malformed. Ignore this laser scan. what(): %s", ex.what());
//     return; //ignore this message
//   }

//   // buffer the point cloud
//   buffer->lock();
//   buffer->bufferCloud(cloud);
//   buffer->unlock();
// }

// void ObstacleLayer::laserScanValidInfCallback(const sensor_msgs::LaserScanConstPtr& raw_message,
//                                               const boost::shared_ptr<ObservationBuffer>& buffer)
// {
//   // Filter positive infinities ("Inf"s) to max_range.
//   float epsilon = 0.0001;  // a tenth of a millimeter
//   sensor_msgs::LaserScan message = *raw_message;
//   for (size_t i = 0; i < message.ranges.size(); i++)
//   {
//     float range = message.ranges[ i ];
//     if (!std::isfinite(range) && range > 0)
//     {
//       message.ranges[ i ] = message.range_max - epsilon;
//     }
//   }

//   // project the laser into a point cloud
//   sensor_msgs::PointCloud2 cloud;
//   cloud.header = message.header;

//   // project the scan into a point cloud
//   try
//   {
//     projector_.transformLaserScanToPointCloud(message.header.frame_id, message, cloud, *tf_);
//   }
//   catch (tf2::TransformException &ex)
//   {
//     ROS_WARN("High fidelity enabled, but TF returned a transform exception to frame %s: %s",
//              global_frame_.c_str(), ex.what());
//     projector_.projectLaser(message, cloud);
//   }
//   catch (std::runtime_error &ex)
//   {
//     ROS_WARN("transformLaserScanToPointCloud error, it seems the message from laser sensor is malformed. Ignore this laser scan. what(): %s", ex.what());
//     return; //ignore this message
//   }

//   // buffer the point cloud
//   buffer->lock();
//   buffer->bufferCloud(cloud);
//   buffer->unlock();
// }

// void ObstacleLayer::pointCloudCallback(const sensor_msgs::PointCloudConstPtr& message,
//                                                const boost::shared_ptr<ObservationBuffer>& buffer)
// {
//   sensor_msgs::PointCloud2 cloud2;

//   if (!sensor_msgs::convertPointCloudToPointCloud2(*message, cloud2))
//   {
//     ROS_ERROR("Failed to convert a PointCloud to a PointCloud2, dropping message");
//     return;
//   }

//   // buffer the point cloud
//   buffer->lock();
//   buffer->bufferCloud(cloud2);
//   buffer->unlock();
// }

// void ObstacleLayer::pointCloud2Callback(const sensor_msgs::PointCloud2ConstPtr& message,
//                                                 const boost::shared_ptr<ObservationBuffer>& buffer)
// {
//   // buffer the point cloud
//   buffer->lock();
//   buffer->bufferCloud(*message);
//   buffer->unlock();
// }

void ObstacleLayer::updateBounds(double robot_x, double robot_y, double robot_yaw, double* min_x,
                                          double* min_y, double* max_x, double* max_y)
{
  if (rolling_window_)
    updateOrigin(robot_x - getSizeInMetersX() / 2, robot_y - getSizeInMetersY() / 2);
  useExtraBounds(min_x, min_y, max_x, max_y);

  bool current = true;
  std::vector<Observation> observations, clearing_observations;

  // get the marking observations
  current = current && getMarkingObservations(observations);

  // get the clearing observations
  current = current && getClearingObservations(clearing_observations);

  // update the global current status
  current_ = current;

  // raytrace freespace
  for (unsigned int i = 0; i < clearing_observations.size(); ++i)
  {
    raytraceFreespace(clearing_observations[i], min_x, min_y, max_x, max_y);
  }

  // place the new obstacles into a priority queue... each with a priority of zero to begin with
  for (std::vector<Observation>::const_iterator it = observations.begin(); it != observations.end(); ++it)
  {
    const Observation& obs = *it;

    const sensor_msgs::PointCloud2& cloud = *(obs.cloud_);

    double sq_obstacle_range = obs.obstacle_range_ * obs.obstacle_range_;

    sensor_msgs::PointCloud2ConstIterator<float> iter_x(cloud, "x");
    sensor_msgs::PointCloud2ConstIterator<float> iter_y(cloud, "y");
    sensor_msgs::PointCloud2ConstIterator<float> iter_z(cloud, "z");

    for (; iter_x !=iter_x.end(); ++iter_x, ++iter_y, ++iter_z)
    {
      double px = *iter_x, py = *iter_y, pz = *iter_z;

      // if the obstacle is too high or too far away from the robot we won't add it
      if (pz > max_obstacle_height_)
      {
        printf("The point is too high");
        continue;
      }

      // compute the squared distance from the hitpoint to the pointcloud's origin
      double sq_dist = (px - obs.origin_.x) * (px - obs.origin_.x) + (py - obs.origin_.y) * (py - obs.origin_.y)
          + (pz - obs.origin_.z) * (pz - obs.origin_.z);

      // if the point is far enough away... we won't consider it
      if (sq_dist >= sq_obstacle_range)
      {
        printf("The point is too far away");
        continue;
      }

      // now we need to compute the map coordinates for the observation
      unsigned int mx, my;
      if (!worldToMap(px, py, mx, my))
      {
        printf("Computing map coords failed");
        continue;
      }

      unsigned int index = getIndex(mx, my);
      costmap_[index] = LETHAL_OBSTACLE;
      touch(px, py, min_x, min_y, max_x, max_y);
    }
  }

  updateFootprint(robot_x, robot_y, robot_yaw, min_x, min_y, max_x, max_y);
}

void ObstacleLayer::updateFootprint(double robot_x, double robot_y, double robot_yaw, double* min_x, double* min_y,
                                    double* max_x, double* max_y)
{
    if (!footprint_clearing_enabled_) return;
    transformFootprint(robot_x, robot_y, robot_yaw, getFootprint(), transformed_footprint_);

    for (unsigned int i = 0; i < transformed_footprint_.size(); i++)
    {
      touch(transformed_footprint_[i].x, transformed_footprint_[i].y, min_x, min_y, max_x, max_y);
    }
}

void ObstacleLayer::updateCosts(costmap_2d::Costmap2D& master_grid, int min_i, int min_j, int max_i, int max_j)
{
  if (footprint_clearing_enabled_)
  {
    setConvexPolygonCost(transformed_footprint_, costmap_2d::FREE_SPACE);
  }
  
  switch (combination_method_)
  {
    case 0:  // Overwrite
      updateWithOverwrite(master_grid, min_i, min_j, max_i, max_j);
      break;
    case 1:  // Maximum
      updateWithMax(master_grid, min_i, min_j, max_i, max_j);
      break;
    default:  // Nothing
      break;
  }

}

void ObstacleLayer::addStaticObservation(costmap_2d::Observation& obs, bool marking, bool clearing)
{
  if (marking)
    static_marking_observations_.push_back(obs);
  if (clearing)
    static_clearing_observations_.push_back(obs);
}

void ObstacleLayer::clearStaticObservations(bool marking, bool clearing)
{
  if (marking)
    static_marking_observations_.clear();
  if (clearing)
    static_clearing_observations_.clear();
}

bool ObstacleLayer::getMarkingObservations(std::vector<Observation>& marking_observations) const
{
  bool current = true;
  // get the marking observations
  for (unsigned int i = 0; i < marking_buffers_.size(); ++i)
  {
    marking_buffers_[i]->lock();
    marking_buffers_[i]->getObservations(marking_observations);
    current = marking_buffers_[i]->isCurrent() && current;
    marking_buffers_[i]->unlock();
  }
  marking_observations.insert(marking_observations.end(),
                              static_marking_observations_.begin(), static_marking_observations_.end());
  return current;
}

bool ObstacleLayer::getClearingObservations(std::vector<Observation>& clearing_observations) const
{
  bool current = true;
  // get the clearing observations
  for (unsigned int i = 0; i < clearing_buffers_.size(); ++i)
  {
    clearing_buffers_[i]->lock();
    clearing_buffers_[i]->getObservations(clearing_observations);
    current = clearing_buffers_[i]->isCurrent() && current;
    clearing_buffers_[i]->unlock();
  }
  clearing_observations.insert(clearing_observations.end(),
                              static_clearing_observations_.begin(), static_clearing_observations_.end());
  return current;
}

void ObstacleLayer::raytraceFreespace(const Observation& clearing_observation, double* min_x, double* min_y,
                                              double* max_x, double* max_y)
{
  double ox = clearing_observation.origin_.x;
  double oy = clearing_observation.origin_.y;
  const sensor_msgs::PointCloud2 &cloud = *(clearing_observation.cloud_);

  // get the map coordinates of the origin of the sensor
  unsigned int x0, y0;
  if (!worldToMap(ox, oy, x0, y0))
  {
    printf(
        "The origin for the sensor at (%.2f, %.2f) is out of map bounds. So, the costmap cannot raytrace for it.",
        ox, oy);
    return;
  }

  // we can pre-compute the enpoints of the map outside of the inner loop... we'll need these later
  double origin_x = origin_x_, origin_y = origin_y_;
  double map_end_x = origin_x + size_x_ * resolution_;
  double map_end_y = origin_y + size_y_ * resolution_;


  touch(ox, oy, min_x, min_y, max_x, max_y);

  // for each point in the cloud, we want to trace a line from the origin and clear obstacles along it
  sensor_msgs::PointCloud2ConstIterator<float> iter_x(cloud, "x");
  sensor_msgs::PointCloud2ConstIterator<float> iter_y(cloud, "y");

  for (; iter_x != iter_x.end(); ++iter_x, ++iter_y)
  {
    double wx = *iter_x;
    double wy = *iter_y;

    // now we also need to make sure that the enpoint we're raytracing
    // to isn't off the costmap and scale if necessary
    double a = wx - ox;
    double b = wy - oy;

    // the minimum value to raytrace from is the origin
    if (wx < origin_x)
    {
      double t = (origin_x - ox) / a;
      wx = origin_x;
      wy = oy + b * t;
    }
    if (wy < origin_y)
    {
      double t = (origin_y - oy) / b;
      wx = ox + a * t;
      wy = origin_y;
    }

    // the maximum value to raytrace to is the end of the map
    if (wx > map_end_x)
    {
      double t = (map_end_x - ox) / a;
      wx = map_end_x - .001;
      wy = oy + b * t;
    }
    if (wy > map_end_y)
    {
      double t = (map_end_y - oy) / b;
      wx = ox + a * t;
      wy = map_end_y - .001;
    }

    // now that the vector is scaled correctly... we'll get the map coordinates of its endpoint
    unsigned int x1, y1;

    // check for legality just in case
    if (!worldToMap(wx, wy, x1, y1))
      continue;

    unsigned int cell_raytrace_range = cellDistance(clearing_observation.raytrace_range_);
    MarkCell marker(costmap_, FREE_SPACE);
    // and finally... we can execute our trace to clear obstacles along that line
    raytraceLine(marker, x0, y0, x1, y1, cell_raytrace_range);

    updateRaytraceBounds(ox, oy, wx, wy, clearing_observation.raytrace_range_, min_x, min_y, max_x, max_y);
  }
}

// void ObstacleLayer::activate()
// {
//   // if we're stopped we need to re-subscribe to topics
//   for (unsigned int i = 0; i < observation_subscribers_.size(); ++i)
//   {
//     if (observation_subscribers_[i] != NULL)
//       observation_subscribers_[i]->subscribe();
//   }

//   for (unsigned int i = 0; i < observation_buffers_.size(); ++i)
//   {
//     if (observation_buffers_[i])
//       observation_buffers_[i]->resetLastUpdated();
//   }
// }
// void ObstacleLayer::deactivate()
// {
//   for (unsigned int i = 0; i < observation_subscribers_.size(); ++i)
//   {
//     if (observation_subscribers_[i] != NULL)
//       observation_subscribers_[i]->unsubscribe();
//   }
// }

void ObstacleLayer::updateRaytraceBounds(double ox, double oy, double wx, double wy, double range,
                                         double* min_x, double* min_y, double* max_x, double* max_y)
{
  double dx = wx-ox, dy = wy-oy;
  double full_distance = hypot(dx, dy);
  double scale = std::min(1.0, range / full_distance);
  double ex = ox + dx * scale, ey = oy + dy * scale;
  touch(ex, ey, min_x, min_y, max_x, max_y);
}

// void ObstacleLayer::reset()
// {
//     deactivate();
//     resetMaps();
//     current_ = true;
//     activate();
// }

// Export factory function
static PluginPtr create_obstacle_plugin() {
    return std::make_shared<ObstacleLayer>();
}

// Alias cho Boost.DLL (nếu muốn dùng boost::dll::import_alias)
BOOST_DLL_ALIAS(create_obstacle_plugin, create_plugin)

}  // namespace costmap_2d