528 lines
18 KiB
C++
528 lines
18 KiB
C++
#include <costmap_2d/obstacle_layer.h>
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#include <costmap_2d/costmap_math.h>
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#include <costmap_2d/utils.h>
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#include <sensor_msgs/point_cloud2_iterator.h>
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#include <tf2/convert.h>
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#include <tf2/utils.h>
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#include <boost/dll/alias.hpp>
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using costmap_2d::NO_INFORMATION;
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using costmap_2d::LETHAL_OBSTACLE;
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using costmap_2d::FREE_SPACE;
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using costmap_2d::ObservationBuffer;
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using costmap_2d::Observation;
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namespace costmap_2d
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{
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void ObstacleLayer::onInitialize()
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{
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rolling_window_ = layered_costmap_->isRolling();
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ObstacleLayer::matchSize();
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current_ = true;
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stop_receiving_data_ = false;
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global_frame_ = layered_costmap_->getGlobalFrameID();
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getParams();
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}
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ObstacleLayer::~ObstacleLayer()
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{}
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bool ObstacleLayer::getParams()
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{
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try {
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YAML::Node config = YAML::LoadFile("/home/duongtd/robotics_core/costmap_2d/config/config.yaml");
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YAML::Node layer = config["obstacle_layer"];
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bool track_unknown_space = loadParam(layer, "track_unknown_space", layered_costmap_->isTrackingUnknown());
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if (track_unknown_space)
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default_value_ = NO_INFORMATION;
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else
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default_value_ = FREE_SPACE;
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double transform_tolerance = loadParam(layer,"transform_tolerance", 0.2);
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// get the topics that we'll subscribe to from the parameter server
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std::string topics_string = loadParam(layer,"observation_sources", std::string(""));
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printf(" Subscribed to Topics: %s\n", topics_string.c_str());
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// get the parameters for the specific topic
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double observation_keep_time = 0, expected_update_rate = 0, min_obstacle_height = 0, max_obstacle_height = 2;
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std::string topic = "map", sensor_frame = "laser_frame", data_type = "PointCloud";
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bool inf_is_valid = false, clearing=false, marking=true;
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topic = loadParam(layer,"topic", topic);
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sensor_frame = loadParam(layer,"sensor_frame", std::string(""));
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observation_keep_time = loadParam(layer,"observation_persistence", 0.0);
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expected_update_rate = loadParam(layer,"expected_update_rate", 0.0);
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data_type = loadParam(layer,"data_type", std::string("PointCloud"));
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min_obstacle_height = loadParam(layer,"min_obstacle_height", 0.0);
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max_obstacle_height = loadParam(layer,"max_obstacle_height", 2.0);
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inf_is_valid = loadParam(layer,"inf_is_valid", false);
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clearing = loadParam(layer,"clearing", false);
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marking = loadParam(layer,"marking", true);
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if (!(data_type == "PointCloud2" || data_type == "PointCloud" || data_type == "LaserScan"))
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{
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printf("Only topics that use point clouds or laser scans are currently supported\n");
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throw std::runtime_error("Only topics that use point clouds or laser scans are currently supported");
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}
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std::string raytrace_range_param_name, obstacle_range_param_name;
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double obstacle_range = 2.5;
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obstacle_range = loadParam(layer,"obstacle_range", obstacle_range);
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double raytrace_range = 3.0;
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raytrace_range = loadParam(layer,"raytrace_range", raytrace_range);
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bool footprint_clearing_enabled = loadParam(layer, "footprint_clearing_enabled", true);
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int combination_method = loadParam(layer, "combination_method", 1);
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// enabled_ = enabled;
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footprint_clearing_enabled_ = footprint_clearing_enabled;
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max_obstacle_height_ = max_obstacle_height;
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combination_method_ = combination_method;
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printf("Creating an observation buffer for topic %s, frame %s\n", topic.c_str(),
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sensor_frame.c_str());
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// create an observation buffer
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observation_buffers_.push_back(
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boost::shared_ptr < ObservationBuffer
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> (new ObservationBuffer(topic, observation_keep_time, expected_update_rate, min_obstacle_height,
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max_obstacle_height, obstacle_range, raytrace_range, *tf_, global_frame_,
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sensor_frame, transform_tolerance)));
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if (marking)
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marking_buffers_.push_back(observation_buffers_.back());
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// check if we'll also add this buffer to our clearing observation buffers
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if (clearing)
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clearing_buffers_.push_back(observation_buffers_.back());
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printf(
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"Created an observation buffer for topic %s, global frame: %s, "
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"expected update rate: %.2f, observation persistence: %.2f",
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topic.c_str(), global_frame_.c_str(), expected_update_rate, observation_keep_time);
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}
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catch (const YAML::BadFile& e) {
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std::cerr << "Cannot open YAML file: " << e.what() << std::endl;
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return false;
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}
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return true;
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}
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void ObstacleLayer::handleImpl(const void* data,
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const std::type_info& type,
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const std::string& topic)
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{
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if(!stop_receiving_data_)
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{
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if(observation_buffers_.empty()) return;
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boost::shared_ptr<costmap_2d::ObservationBuffer> buffer = observation_buffers_.back();
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if (type == typeid(sensor_msgs::LaserScan) && topic == "laser") {
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laserScanCallback(*static_cast<const sensor_msgs::LaserScan*>(data), buffer);
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} else if (type == typeid(sensor_msgs::LaserScan) && topic == "laser_valid") {
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laserScanValidInfCallback(*static_cast<const sensor_msgs::LaserScan*>(data), buffer);
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} else if (type == typeid(sensor_msgs::PointCloud) && topic == "pcl_cb") {
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pointCloudCallback(*static_cast<const sensor_msgs::PointCloud*>(data), buffer);
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} else if (type == typeid(sensor_msgs::PointCloud2) && topic == "pcl2_cb") {
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pointCloud2Callback(*static_cast<const sensor_msgs::PointCloud2*>(data), buffer);
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} else {
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std::cout << "[Plugin] Unknown type: " << type.name() << std::endl;
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}
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}
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else
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{
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std::cout << "Stop receiving data!" << std::endl;
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return;
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}
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}
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void ObstacleLayer::laserScanCallback(const sensor_msgs::LaserScan& message,
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const boost::shared_ptr<ObservationBuffer>& buffer)
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{
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// project the laser into a point cloud
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sensor_msgs::PointCloud2 cloud;
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cloud.header = message.header;
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// printf("TEST PLUGIN OBSTACLE!!!\n");
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// project the scan into a point cloud
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try
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{
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projector_.transformLaserScanToPointCloud(message.header.frame_id, message, cloud, *tf_);
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}
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catch (tf2::TransformException &ex)
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{
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printf("High fidelity enabled, but TF returned a transform exception to frame %s: %s\n", global_frame_.c_str(),
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ex.what());
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projector_.projectLaser(message, cloud);
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}
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catch (std::runtime_error &ex)
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{
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printf("transformLaserScanToPointCloud error, it seems the message from laser sensor is malformed. Ignore this laser scan. what(): %s\n", ex.what());
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return; //ignore this message
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}
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// buffer the point cloud
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buffer->lock();
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buffer->bufferCloud(cloud);
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buffer->unlock();
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}
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void ObstacleLayer::laserScanValidInfCallback(const sensor_msgs::LaserScan& raw_message,
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const boost::shared_ptr<ObservationBuffer>& buffer)
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{
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// printf("TEST PLUGIN OBSTACLE 2!!!\n");
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// Filter positive infinities ("Inf"s) to max_range.
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float epsilon = 0.0001; // a tenth of a millimeter
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sensor_msgs::LaserScan message = raw_message;
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for (size_t i = 0; i < message.ranges.size(); i++)
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{
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float range = message.ranges[ i ];
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if (!std::isfinite(range) && range > 0)
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{
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message.ranges[ i ] = message.range_max - epsilon;
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}
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}
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// project the laser into a point cloud
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sensor_msgs::PointCloud2 cloud;
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cloud.header = message.header;
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// project the scan into a point cloud
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try
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{
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projector_.transformLaserScanToPointCloud(message.header.frame_id, message, cloud, *tf_);
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}
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catch (tf2::TransformException &ex)
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{
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printf("High fidelity enabled, but TF returned a transform exception to frame %s: %s\n",
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global_frame_.c_str(), ex.what());
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projector_.projectLaser(message, cloud);
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}
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catch (std::runtime_error &ex)
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{
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printf("transformLaserScanToPointCloud error, it seems the message from laser sensor is malformed. Ignore this laser scan. what(): %s\n", ex.what());
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return; //ignore this message
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}
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// buffer the point cloud
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buffer->lock();
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buffer->bufferCloud(cloud);
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buffer->unlock();
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}
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void ObstacleLayer::pointCloudCallback(const sensor_msgs::PointCloud& message,
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const boost::shared_ptr<ObservationBuffer>& buffer)
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{
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// printf("TEST PLUGIN OBSTACLE 3!!!\n");
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sensor_msgs::PointCloud2 cloud2;
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if (!sensor_msgs::convertPointCloudToPointCloud2(message, cloud2))
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{
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printf("Failed to convert a PointCloud to a PointCloud2, dropping message\n");
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return;
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}
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// buffer the point cloud
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buffer->lock();
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buffer->bufferCloud(cloud2);
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buffer->unlock();
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}
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void ObstacleLayer::pointCloud2Callback(const sensor_msgs::PointCloud2& message,
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const boost::shared_ptr<ObservationBuffer>& buffer)
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{
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// buffer the point cloud
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buffer->lock();
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buffer->bufferCloud(message);
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buffer->unlock();
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}
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void ObstacleLayer::updateBounds(double robot_x, double robot_y, double robot_yaw, double* min_x,
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double* min_y, double* max_x, double* max_y)
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{
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if (rolling_window_)
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updateOrigin(robot_x - getSizeInMetersX() / 2, robot_y - getSizeInMetersY() / 2);
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useExtraBounds(min_x, min_y, max_x, max_y);
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bool current = true;
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std::vector<Observation> observations, clearing_observations;
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// get the marking observations
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current = current && getMarkingObservations(observations);
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// get the clearing observations
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current = current && getClearingObservations(clearing_observations);
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// update the global current status
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current_ = current;
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// raytrace freespace
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for (unsigned int i = 0; i < clearing_observations.size(); ++i)
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{
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raytraceFreespace(clearing_observations[i], min_x, min_y, max_x, max_y);
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}
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// place the new obstacles into a priority queue... each with a priority of zero to begin with
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for (std::vector<Observation>::const_iterator it = observations.begin(); it != observations.end(); ++it)
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{
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const Observation& obs = *it;
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const sensor_msgs::PointCloud2& cloud = *(obs.cloud_);
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double sq_obstacle_range = obs.obstacle_range_ * obs.obstacle_range_;
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sensor_msgs::PointCloud2ConstIterator<float> iter_x(cloud, "x");
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sensor_msgs::PointCloud2ConstIterator<float> iter_y(cloud, "y");
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sensor_msgs::PointCloud2ConstIterator<float> iter_z(cloud, "z");
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for (; iter_x !=iter_x.end(); ++iter_x, ++iter_y, ++iter_z)
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{
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double px = *iter_x, py = *iter_y, pz = *iter_z;
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// if the obstacle is too high or too far away from the robot we won't add it
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if (pz > max_obstacle_height_)
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{
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printf("The point is too high\n");
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continue;
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}
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// compute the squared distance from the hitpoint to the pointcloud's origin
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double sq_dist = (px - obs.origin_.x) * (px - obs.origin_.x) + (py - obs.origin_.y) * (py - obs.origin_.y)
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+ (pz - obs.origin_.z) * (pz - obs.origin_.z);
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// if the point is far enough away... we won't consider it
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if (sq_dist >= sq_obstacle_range)
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{
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printf("The point is too far away\n");
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continue;
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}
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// now we need to compute the map coordinates for the observation
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unsigned int mx, my;
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if (!worldToMap(px, py, mx, my))
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{
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printf("Computing map coords failed\n");
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continue;
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}
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unsigned int index = getIndex(mx, my);
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costmap_[index] = LETHAL_OBSTACLE;
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touch(px, py, min_x, min_y, max_x, max_y);
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}
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}
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updateFootprint(robot_x, robot_y, robot_yaw, min_x, min_y, max_x, max_y);
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}
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void ObstacleLayer::updateFootprint(double robot_x, double robot_y, double robot_yaw, double* min_x, double* min_y,
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double* max_x, double* max_y)
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{
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if (!footprint_clearing_enabled_) return;
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transformFootprint(robot_x, robot_y, robot_yaw, getFootprint(), transformed_footprint_);
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for (unsigned int i = 0; i < transformed_footprint_.size(); i++)
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{
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touch(transformed_footprint_[i].x, transformed_footprint_[i].y, min_x, min_y, max_x, max_y);
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}
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}
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void ObstacleLayer::updateCosts(costmap_2d::Costmap2D& master_grid, int min_i, int min_j, int max_i, int max_j)
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{
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if (footprint_clearing_enabled_)
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{
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setConvexPolygonCost(transformed_footprint_, costmap_2d::FREE_SPACE);
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}
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switch (combination_method_)
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{
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case 0: // Overwrite
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updateWithOverwrite(master_grid, min_i, min_j, max_i, max_j);
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break;
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case 1: // Maximum
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updateWithMax(master_grid, min_i, min_j, max_i, max_j);
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break;
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default: // Nothing
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break;
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}
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}
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void ObstacleLayer::addStaticObservation(costmap_2d::Observation& obs, bool marking, bool clearing)
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{
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if (marking)
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static_marking_observations_.push_back(obs);
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if (clearing)
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static_clearing_observations_.push_back(obs);
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}
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void ObstacleLayer::clearStaticObservations(bool marking, bool clearing)
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{
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if (marking)
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static_marking_observations_.clear();
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if (clearing)
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static_clearing_observations_.clear();
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}
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bool ObstacleLayer::getMarkingObservations(std::vector<Observation>& marking_observations) const
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{
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bool current = true;
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// get the marking observations
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for (unsigned int i = 0; i < marking_buffers_.size(); ++i)
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{
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marking_buffers_[i]->lock();
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marking_buffers_[i]->getObservations(marking_observations);
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current = marking_buffers_[i]->isCurrent() && current;
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marking_buffers_[i]->unlock();
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}
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marking_observations.insert(marking_observations.end(),
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static_marking_observations_.begin(), static_marking_observations_.end());
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return current;
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}
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bool ObstacleLayer::getClearingObservations(std::vector<Observation>& clearing_observations) const
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{
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bool current = true;
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// get the clearing observations
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for (unsigned int i = 0; i < clearing_buffers_.size(); ++i)
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{
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clearing_buffers_[i]->lock();
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clearing_buffers_[i]->getObservations(clearing_observations);
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current = clearing_buffers_[i]->isCurrent() && current;
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clearing_buffers_[i]->unlock();
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}
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clearing_observations.insert(clearing_observations.end(),
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static_clearing_observations_.begin(), static_clearing_observations_.end());
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return current;
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}
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void ObstacleLayer::raytraceFreespace(const Observation& clearing_observation, double* min_x, double* min_y,
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double* max_x, double* max_y)
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{
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double ox = clearing_observation.origin_.x;
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double oy = clearing_observation.origin_.y;
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const sensor_msgs::PointCloud2 &cloud = *(clearing_observation.cloud_);
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// get the map coordinates of the origin of the sensor
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unsigned int x0, y0;
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if (!worldToMap(ox, oy, x0, y0))
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{
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printf(
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"The origin for the sensor at (%.2f, %.2f) is out of map bounds. So, the costmap cannot raytrace for it.\n",
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ox, oy);
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return;
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}
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// we can pre-compute the enpoints of the map outside of the inner loop... we'll need these later
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double origin_x = origin_x_, origin_y = origin_y_;
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double map_end_x = origin_x + size_x_ * resolution_;
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double map_end_y = origin_y + size_y_ * resolution_;
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touch(ox, oy, min_x, min_y, max_x, max_y);
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// for each point in the cloud, we want to trace a line from the origin and clear obstacles along it
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sensor_msgs::PointCloud2ConstIterator<float> iter_x(cloud, "x");
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sensor_msgs::PointCloud2ConstIterator<float> iter_y(cloud, "y");
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for (; iter_x != iter_x.end(); ++iter_x, ++iter_y)
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{
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double wx = *iter_x;
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double wy = *iter_y;
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// now we also need to make sure that the enpoint we're raytracing
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// to isn't off the costmap and scale if necessary
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double a = wx - ox;
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double b = wy - oy;
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// the minimum value to raytrace from is the origin
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if (wx < origin_x)
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{
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double t = (origin_x - ox) / a;
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wx = origin_x;
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wy = oy + b * t;
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}
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if (wy < origin_y)
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{
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double t = (origin_y - oy) / b;
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wx = ox + a * t;
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wy = origin_y;
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}
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// the maximum value to raytrace to is the end of the map
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if (wx > map_end_x)
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{
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double t = (map_end_x - ox) / a;
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wx = map_end_x - .001;
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wy = oy + b * t;
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}
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if (wy > map_end_y)
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{
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double t = (map_end_y - oy) / b;
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wx = ox + a * t;
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wy = map_end_y - .001;
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}
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// now that the vector is scaled correctly... we'll get the map coordinates of its endpoint
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unsigned int x1, y1;
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// check for legality just in case
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if (!worldToMap(wx, wy, x1, y1))
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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()
|
|
{
|
|
stop_receiving_data_ = false;
|
|
for (unsigned int i = 0; i < observation_buffers_.size(); ++i)
|
|
{
|
|
if (observation_buffers_[i])
|
|
observation_buffers_[i]->resetLastUpdated();
|
|
}
|
|
}
|
|
void ObstacleLayer::deactivate()
|
|
{
|
|
stop_receiving_data_ = true;
|
|
}
|
|
|
|
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 PluginCostmapLayerPtr 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
|