obstacle_layer.cpp

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 * Author: Eitan Marder-Eppstein
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#include <costmap_2d/obstacle_layer.h>
#include <costmap_2d/costmap_math.h>
#include <tf2_ros/message_filter.h>
 
#include <pluginlib/class_list_macros.hpp>
#include <sensor_msgs/point_cloud2_iterator.h>
 
PLUGINLIB_EXPORT_CLASS(costmap_2d::ObstacleLayer, costmap_2d::Layer)
 
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()
{
  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);
    }
 
    ROS_DEBUG("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());
 
    ROS_DEBUG(
        "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()
{
    if (dsrv_)
        delete dsrv_;
}
void ObstacleLayer::reconfigureCB(costmap_2d::ObstaclePluginConfig &config, uint32_t level)
{
  enabled_ = config.enabled;
  footprint_clearing_enabled_ = config.footprint_clearing_enabled;
  max_obstacle_height_ = config.max_obstacle_height;
  combination_method_ = config.combination_method;
}
 
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_)
      {
        ROS_DEBUG("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)
      {
        ROS_DEBUG("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))
      {
        ROS_DEBUG("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))
  {
    ROS_WARN_THROTTLE(
        1.0, "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();
}
 
}  // namespace costmap_2d