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costmap_2d/plugins/obstacle_layer.cpp

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#include <costmap_2d/obstacle_layer.h>
#include <costmap_2d/costmap_math.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()
{
// 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()
{}
// 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_)
{
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
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