observation_buffer.cpp

Go to the documentation of this file.

/*********************************************************************
*
* Software License Agreement (BSD License)
*
*  Copyright (c) 2008, Willow Garage, Inc.
*  All rights reserved.
*
*  Redistribution and use in source and binary forms, with or without
*  modification, are permitted provided that the following conditions
*  are met:
*
*   * Redistributions of source code must retain the above copyright
*     notice, this list of conditions and the following disclaimer.
*   * Redistributions in binary form must reproduce the above
*     copyright notice, this list of conditions and the following
*     disclaimer in the documentation and/or other materials provided
*     with the distribution.
*   * Neither the name of the Willow Garage nor the names of its
*     contributors may be used to endorse or promote products derived
*     from this software without specific prior written permission.
*
*  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
*  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
*  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
*  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
*  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
*  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
*  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
*  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
*  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
*  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
*  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
*  POSSIBILITY OF SUCH DAMAGE.
*
* Author: Eitan Marder-Eppstein
*********************************************************************/
#include <costmap_2d/observation_buffer.h>

using namespace std;
using namespace tf;

namespace costmap_2d {
  ObservationBuffer::ObservationBuffer(string topic_name, double observation_keep_time, double expected_update_rate, 
      double min_obstacle_height, double max_obstacle_height, double obstacle_range, double raytrace_range,
      TransformListener& tf, string global_frame, string sensor_frame, double tf_tolerance) : tf_(tf),
  observation_keep_time_(observation_keep_time), expected_update_rate_(expected_update_rate), last_updated_(ros::Time::now()),
  global_frame_(global_frame), sensor_frame_(sensor_frame), topic_name_(topic_name), min_obstacle_height_(min_obstacle_height),
  max_obstacle_height_(max_obstacle_height), obstacle_range_(obstacle_range), raytrace_range_(raytrace_range), tf_tolerance_(tf_tolerance)
  {
  }

  ObservationBuffer::~ObservationBuffer(){}

  bool ObservationBuffer::setGlobalFrame(const std::string new_global_frame){
    ros::Time transform_time = ros::Time::now();
    std::string tf_error;

    if(!tf_.waitForTransform(new_global_frame, global_frame_, transform_time, ros::Duration(tf_tolerance_), ros::Duration(0.01), &tf_error)){
      ROS_ERROR("Transform between %s and %s with tolerance %.2f failed: %s.", new_global_frame.c_str(), global_frame_.c_str(), tf_tolerance_, tf_error.c_str());
      return false;
    }

    list<Observation>::iterator obs_it;
    for(obs_it = observation_list_.begin(); obs_it != observation_list_.end(); ++obs_it){
      try{
        Observation& obs = *obs_it;

        geometry_msgs::PointStamped origin;
        origin.header.frame_id = global_frame_;
        origin.header.stamp = transform_time;
        origin.point = obs.origin_;

        //we need to transform the origin of the observation to the new global frame
        tf_.transformPoint(new_global_frame, origin, origin);
        obs.origin_ = origin.point;

        //we also need to transform the cloud of the observation to the new global frame
        pcl_ros::transformPointCloud(new_global_frame, obs.cloud_, obs.cloud_, tf_);

      }
      catch(TransformException& ex){
        ROS_ERROR("TF Error attempting to transform an observation from %s to %s: %s", global_frame_.c_str(), 
            new_global_frame.c_str(), ex.what());
        return false;
      }
    }

    //now we need to update our global_frame member
    global_frame_ = new_global_frame;
    return true;
  }

  void ObservationBuffer::bufferCloud(const sensor_msgs::PointCloud2& cloud){
    try {
      //actually convert the PointCloud2 message into a type we can reason about
      pcl::PointCloud<pcl::PointXYZ> pcl_cloud;
      pcl::fromROSMsg(cloud, pcl_cloud);
      bufferCloud(pcl_cloud);
    }
    catch(pcl::PCLException& ex){
      ROS_ERROR("Failed to convert a message to a pcl type, dropping observation: %s", ex.what());
      return;
    }
  }

  void ObservationBuffer::bufferCloud(const pcl::PointCloud<pcl::PointXYZ>& cloud){
    Stamped<btVector3> global_origin;

    //create a new observation on the list to be populated
    observation_list_.push_front(Observation());

    //check whether the origin frame has been set explicitly or whether we should get it from the cloud
    string origin_frame = sensor_frame_ == "" ? cloud.header.frame_id : sensor_frame_;

    try{
      //given these observations come from sensors... we'll need to store the origin pt of the sensor
      Stamped<btVector3> local_origin(btVector3(0, 0, 0), cloud.header.stamp, origin_frame);
      tf_.transformPoint(global_frame_, local_origin, global_origin);
      observation_list_.front().origin_.x = global_origin.getX();
      observation_list_.front().origin_.y = global_origin.getY();
      observation_list_.front().origin_.z = global_origin.getZ();

      //make sure to pass on the raytrace/obstacle range of the observation buffer to the observations the costmap will see
      observation_list_.front().raytrace_range_ = raytrace_range_;
      observation_list_.front().obstacle_range_ = obstacle_range_;

      pcl::PointCloud<pcl::PointXYZ> global_frame_cloud;

      //transform the point cloud
      pcl_ros::transformPointCloud(global_frame_, cloud, global_frame_cloud, tf_);
      global_frame_cloud.header.stamp = cloud.header.stamp;

      //now we need to remove observations from the cloud that are below or above our height thresholds
      pcl::PointCloud<pcl::PointXYZ>& observation_cloud = observation_list_.front().cloud_;
      unsigned int cloud_size = global_frame_cloud.points.size();
      observation_cloud.points.resize(cloud_size);
      unsigned int point_count = 0;
      
      //copy over the points that are within our height bounds
      for(unsigned int i = 0; i < cloud_size; ++i){
        if(global_frame_cloud.points[i].z <= max_obstacle_height_ && global_frame_cloud.points[i].z >= min_obstacle_height_){
          observation_cloud.points[point_count++] = global_frame_cloud.points[i];
        }
      }

      //resize the cloud for the number of legal points
      observation_cloud.points.resize(point_count);
      observation_cloud.header.stamp = cloud.header.stamp;
      observation_cloud.header.frame_id = global_frame_cloud.header.frame_id;
    }
    catch(TransformException& ex){
      //if an exception occurs, we need to remove the empty observation from the list
      observation_list_.pop_front();
      ROS_ERROR("TF Exception that should never happen for sensor frame: %s, cloud frame: %s, %s", sensor_frame_.c_str(), 
          cloud.header.frame_id.c_str(), ex.what());
      return;
    }

    //if the update was successful, we want to update the last updated time
    last_updated_ = ros::Time::now();

    //we'll also remove any stale observations from the list
    purgeStaleObservations();

  }

  //returns a copy of the observations
  void ObservationBuffer::getObservations(vector<Observation>& observations){
    //first... let's make sure that we don't have any stale observations
    purgeStaleObservations();

    //now we'll just copy the observations for the caller
    list<Observation>::iterator obs_it;
    for(obs_it = observation_list_.begin(); obs_it != observation_list_.end(); ++obs_it){
      observations.push_back(*obs_it);
    }

  }

  void ObservationBuffer::purgeStaleObservations(){
    if(!observation_list_.empty()){
      list<Observation>::iterator obs_it = observation_list_.begin();
      //if we're keeping observations for no time... then we'll only keep one observation
      if(observation_keep_time_ == ros::Duration(0.0)){
        observation_list_.erase(++obs_it, observation_list_.end());
        return;
      }

      //otherwise... we'll have to loop through the observations to see which ones are stale
      for(obs_it = observation_list_.begin(); obs_it != observation_list_.end(); ++obs_it){
        Observation& obs = *obs_it;
        //check if the observation is out of date... and if it is, remove it and those that follow from the list
        ros::Duration time_diff = last_updated_ - obs.cloud_.header.stamp;
        if((last_updated_ - obs.cloud_.header.stamp) > observation_keep_time_){
          observation_list_.erase(obs_it, observation_list_.end());
          return;
        }
      }
    }
  }

  bool ObservationBuffer::isCurrent() const {
    if(expected_update_rate_ == ros::Duration(0.0))
      return true;

    bool current = (ros::Time::now() - last_updated_).toSec() <= expected_update_rate_.toSec();
    if(!current){
      ROS_WARN("The %s observation buffer has not been updated for %.2f seconds, and it should be updated every %.2f seconds.", topic_name_.c_str(),
          (ros::Time::now() - last_updated_).toSec(), expected_update_rate_.toSec());
    }
    return current;
  }

  void ObservationBuffer::resetLastUpdated ()
  {
    last_updated_ = ros::Time::now();
  }
};

---

costmap_2d
Author(s): Eitan Marder-Eppstein
autogenerated on Fri Jan 11 09:34:22 2013