356 lines
12 KiB
C++
356 lines
12 KiB
C++
#include <algorithm>
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#include <costmap_2d/inflation_layer.h>
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#include <costmap_2d/costmap_math.h>
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#include <costmap_2d/footprint.h>
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#include <boost/thread.hpp>
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// PLUGINLIB_EXPORT_CLASS(costmap_2d::InflationLayer, costmap_2d::Layer)
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using costmap_2d::LETHAL_OBSTACLE;
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using costmap_2d::INSCRIBED_INFLATED_OBSTACLE;
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using costmap_2d::NO_INFORMATION;
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namespace costmap_2d
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{
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InflationLayer::InflationLayer()
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: resolution_(0)
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, inflation_radius_(0)
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, inscribed_radius_(0)
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, weight_(0)
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, inflate_unknown_(false)
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, cell_inflation_radius_(0)
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, cached_cell_inflation_radius_(0)
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// , dsrv_(NULL)
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, seen_(NULL)
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, cached_costs_(NULL)
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, cached_distances_(NULL)
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, last_min_x_(-std::numeric_limits<float>::max())
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, last_min_y_(-std::numeric_limits<float>::max())
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, last_max_x_(std::numeric_limits<float>::max())
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, last_max_y_(std::numeric_limits<float>::max())
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{
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inflation_access_ = new boost::recursive_mutex();
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}
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// void InflationLayer::onInitialize()
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// {
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// {
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// boost::unique_lock < boost::recursive_mutex > lock(*inflation_access_);
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// ros::NodeHandle nh("~/" + name_), g_nh;
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// current_ = true;
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// if (seen_)
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// delete[] seen_;
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// seen_ = NULL;
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// seen_size_ = 0;
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// need_reinflation_ = false;
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// dynamic_reconfigure::Server<costmap_2d::InflationPluginConfig>::CallbackType cb =
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// [this](auto& config, auto level){ reconfigureCB(config, level); };
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// if (dsrv_ != NULL){
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// dsrv_->clearCallback();
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// dsrv_->setCallback(cb);
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// }
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// else
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// {
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// dsrv_ = new dynamic_reconfigure::Server<costmap_2d::InflationPluginConfig>(ros::NodeHandle("~/" + name_));
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// dsrv_->setCallback(cb);
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// }
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// }
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// matchSize();
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// }
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// void InflationLayer::reconfigureCB(costmap_2d::InflationPluginConfig &config, uint32_t level)
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// {
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// setInflationParameters(config.inflation_radius, config.cost_scaling_factor);
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// if (enabled_ != config.enabled || inflate_unknown_ != config.inflate_unknown) {
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// enabled_ = config.enabled;
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// inflate_unknown_ = config.inflate_unknown;
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// need_reinflation_ = true;
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// }
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// }
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// void InflationLayer::matchSize()
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// {
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// boost::unique_lock < boost::recursive_mutex > lock(*inflation_access_);
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// costmap_2d::Costmap2D* costmap = layered_costmap_->getCostmap();
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// resolution_ = costmap->getResolution();
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// cell_inflation_radius_ = cellDistance(inflation_radius_);
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// computeCaches();
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// unsigned int size_x = costmap->getSizeInCellsX(), size_y = costmap->getSizeInCellsY();
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// if (seen_)
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// delete[] seen_;
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// seen_size_ = size_x * size_y;
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// seen_ = new bool[seen_size_];
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// }
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// void InflationLayer::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 (need_reinflation_)
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// {
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// last_min_x_ = *min_x;
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// last_min_y_ = *min_y;
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// last_max_x_ = *max_x;
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// last_max_y_ = *max_y;
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// // For some reason when I make these -<double>::max() it does not
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// // work with Costmap2D::worldToMapEnforceBounds(), so I'm using
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// // -<float>::max() instead.
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// *min_x = -std::numeric_limits<float>::max();
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// *min_y = -std::numeric_limits<float>::max();
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// *max_x = std::numeric_limits<float>::max();
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// *max_y = std::numeric_limits<float>::max();
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// need_reinflation_ = false;
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// }
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// else
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// {
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// double tmp_min_x = last_min_x_;
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// double tmp_min_y = last_min_y_;
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// double tmp_max_x = last_max_x_;
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// double tmp_max_y = last_max_y_;
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// last_min_x_ = *min_x;
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// last_min_y_ = *min_y;
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// last_max_x_ = *max_x;
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// last_max_y_ = *max_y;
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// *min_x = std::min(tmp_min_x, *min_x) - inflation_radius_;
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// *min_y = std::min(tmp_min_y, *min_y) - inflation_radius_;
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// *max_x = std::max(tmp_max_x, *max_x) + inflation_radius_;
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// *max_y = std::max(tmp_max_y, *max_y) + inflation_radius_;
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// }
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// }
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// void InflationLayer::onFootprintChanged()
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// {
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// inscribed_radius_ = layered_costmap_->getInscribedRadius();
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// cell_inflation_radius_ = cellDistance(inflation_radius_);
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// computeCaches();
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// need_reinflation_ = true;
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// ROS_DEBUG("InflationLayer::onFootprintChanged(): num footprint points: %lu,"
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// " inscribed_radius_ = %.3f, inflation_radius_ = %.3f",
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// layered_costmap_->getFootprint().size(), inscribed_radius_, inflation_radius_);
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// }
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// void InflationLayer::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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// boost::unique_lock < boost::recursive_mutex > lock(*inflation_access_);
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// if (cell_inflation_radius_ == 0)
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// return;
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// // make sure the inflation list is empty at the beginning of the cycle (should always be true)
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// ROS_ASSERT_MSG(inflation_cells_.empty(), "The inflation list must be empty at the beginning of inflation");
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// unsigned char* master_array = master_grid.getCharMap();
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// unsigned int size_x = master_grid.getSizeInCellsX(), size_y = master_grid.getSizeInCellsY();
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// if (seen_ == NULL) {
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// ROS_WARN("InflationLayer::updateCosts(): seen_ array is NULL");
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// seen_size_ = size_x * size_y;
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// seen_ = new bool[seen_size_];
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// }
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// else if (seen_size_ != size_x * size_y)
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// {
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// ROS_WARN("InflationLayer::updateCosts(): seen_ array size is wrong");
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// delete[] seen_;
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// seen_size_ = size_x * size_y;
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// seen_ = new bool[seen_size_];
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// }
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// memset(seen_, false, size_x * size_y * sizeof(bool));
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// // We need to include in the inflation cells outside the bounding
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// // box min_i...max_j, by the amount cell_inflation_radius_. Cells
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// // up to that distance outside the box can still influence the costs
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// // stored in cells inside the box.
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// min_i -= cell_inflation_radius_;
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// min_j -= cell_inflation_radius_;
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// max_i += cell_inflation_radius_;
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// max_j += cell_inflation_radius_;
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// min_i = std::max(0, min_i);
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// min_j = std::max(0, min_j);
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// max_i = std::min(int(size_x), max_i);
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// max_j = std::min(int(size_y), max_j);
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// // Inflation list; we append cells to visit in a list associated with its distance to the nearest obstacle
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// // We use a map<distance, list> to emulate the priority queue used before, with a notable performance boost
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// // Start with lethal obstacles: by definition distance is 0.0
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// std::vector<CellData>& obs_bin = inflation_cells_[0.0];
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// for (int j = min_j; j < max_j; j++)
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// {
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// for (int i = min_i; i < max_i; i++)
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// {
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// int index = master_grid.getIndex(i, j);
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// unsigned char cost = master_array[index];
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// if (cost == LETHAL_OBSTACLE)
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// {
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// obs_bin.push_back(CellData(index, i, j, i, j));
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// }
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// }
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// }
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// // Process cells by increasing distance; new cells are appended to the corresponding distance bin, so they
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// // can overtake previously inserted but farther away cells
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// std::map<double, std::vector<CellData> >::iterator bin;
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// for (bin = inflation_cells_.begin(); bin != inflation_cells_.end(); ++bin)
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// {
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// for (int i = 0; i < bin->second.size(); ++i)
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// {
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// // process all cells at distance dist_bin.first
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// const CellData& cell = bin->second[i];
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// unsigned int index = cell.index_;
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// // ignore if already visited
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// if (seen_[index])
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// {
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// continue;
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// }
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// seen_[index] = true;
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// unsigned int mx = cell.x_;
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// unsigned int my = cell.y_;
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// unsigned int sx = cell.src_x_;
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// unsigned int sy = cell.src_y_;
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// // assign the cost associated with the distance from an obstacle to the cell
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// unsigned char cost = costLookup(mx, my, sx, sy);
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// unsigned char old_cost = master_array[index];
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// if (old_cost == NO_INFORMATION && (inflate_unknown_ ? (cost > FREE_SPACE) : (cost >= INSCRIBED_INFLATED_OBSTACLE)))
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// master_array[index] = cost;
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// else
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// master_array[index] = std::max(old_cost, cost);
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// // attempt to put the neighbors of the current cell onto the inflation list
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// if (mx > 0)
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// enqueue(index - 1, mx - 1, my, sx, sy);
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// if (my > 0)
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// enqueue(index - size_x, mx, my - 1, sx, sy);
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// if (mx < size_x - 1)
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// enqueue(index + 1, mx + 1, my, sx, sy);
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// if (my < size_y - 1)
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// enqueue(index + size_x, mx, my + 1, sx, sy);
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// }
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// }
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// inflation_cells_.clear();
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// }
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// /**
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// * @brief Given an index of a cell in the costmap, place it into a list pending for obstacle inflation
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// * @param grid The costmap
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// * @param index The index of the cell
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// * @param mx The x coordinate of the cell (can be computed from the index, but saves time to store it)
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// * @param my The y coordinate of the cell (can be computed from the index, but saves time to store it)
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// * @param src_x The x index of the obstacle point inflation started at
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// * @param src_y The y index of the obstacle point inflation started at
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// */
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// inline void InflationLayer::enqueue(unsigned int index, unsigned int mx, unsigned int my,
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// unsigned int src_x, unsigned int src_y)
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// {
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// if (!seen_[index])
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// {
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// // we compute our distance table one cell further than the inflation radius dictates so we can make the check below
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// double distance = distanceLookup(mx, my, src_x, src_y);
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// // we only want to put the cell in the list if it is within the inflation radius of the obstacle point
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// if (distance > cell_inflation_radius_)
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// return;
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// // push the cell data onto the inflation list and mark
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// inflation_cells_[distance].push_back(CellData(index, mx, my, src_x, src_y));
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// }
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// }
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// void InflationLayer::computeCaches()
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// {
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// if (cell_inflation_radius_ == 0)
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// return;
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// // based on the inflation radius... compute distance and cost caches
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// if (cell_inflation_radius_ != cached_cell_inflation_radius_)
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// {
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// deleteKernels();
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// cached_costs_ = new unsigned char*[cell_inflation_radius_ + 2];
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// cached_distances_ = new double*[cell_inflation_radius_ + 2];
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// for (unsigned int i = 0; i <= cell_inflation_radius_ + 1; ++i)
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// {
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// cached_costs_[i] = new unsigned char[cell_inflation_radius_ + 2];
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// cached_distances_[i] = new double[cell_inflation_radius_ + 2];
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// for (unsigned int j = 0; j <= cell_inflation_radius_ + 1; ++j)
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// {
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// cached_distances_[i][j] = hypot(i, j);
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// }
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// }
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// cached_cell_inflation_radius_ = cell_inflation_radius_;
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// }
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// for (unsigned int i = 0; i <= cell_inflation_radius_ + 1; ++i)
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// {
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// for (unsigned int j = 0; j <= cell_inflation_radius_ + 1; ++j)
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// {
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// cached_costs_[i][j] = computeCost(cached_distances_[i][j]);
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// }
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// }
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// }
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// void InflationLayer::deleteKernels()
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// {
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// if (cached_distances_ != NULL)
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// {
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// for (unsigned int i = 0; i <= cached_cell_inflation_radius_ + 1; ++i)
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// {
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// if (cached_distances_[i])
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// delete[] cached_distances_[i];
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// }
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// if (cached_distances_)
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// delete[] cached_distances_;
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// cached_distances_ = NULL;
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// }
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// if (cached_costs_ != NULL)
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// {
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// for (unsigned int i = 0; i <= cached_cell_inflation_radius_ + 1; ++i)
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// {
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// if (cached_costs_[i])
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// delete[] cached_costs_[i];
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// }
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// delete[] cached_costs_;
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// cached_costs_ = NULL;
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// }
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// }
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// void InflationLayer::setInflationParameters(double inflation_radius, double cost_scaling_factor)
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// {
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// if (weight_ != cost_scaling_factor || inflation_radius_ != inflation_radius)
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// {
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// // Lock here so that reconfiguring the inflation radius doesn't cause segfaults
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// // when accessing the cached arrays
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// boost::unique_lock < boost::recursive_mutex > lock(*inflation_access_);
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// inflation_radius_ = inflation_radius;
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// cell_inflation_radius_ = cellDistance(inflation_radius_);
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// weight_ = cost_scaling_factor;
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// need_reinflation_ = true;
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// computeCaches();
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// }
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// }
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// Export factory function
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static PluginPtr create_inflation_plugin() {
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return std::make_shared<InflationLayer>();
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}
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// Alias cho Boost.DLL (nếu muốn dùng boost::dll::import_alias)
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BOOST_DLL_ALIAS(create_inflation_plugin, create_plugin)
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} // namespace costmap_2d
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