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Lu!! *********************************************************************/ #include "nav2_costmap_2d/inflation_layer.hpp" #include #include #include #include #include #include "nav2_costmap_2d/costmap_math.hpp" #include "nav2_costmap_2d/footprint.hpp" #include "pluginlib/class_list_macros.hpp" #include "rclcpp/parameter_events_filter.hpp" PLUGINLIB_EXPORT_CLASS(nav2_costmap_2d::InflationLayer, nav2_costmap_2d::Layer) using nav2_costmap_2d::LETHAL_OBSTACLE; using nav2_costmap_2d::INSCRIBED_INFLATED_OBSTACLE; using nav2_costmap_2d::NO_INFORMATION; using rcl_interfaces::msg::ParameterType; namespace nav2_costmap_2d { InflationLayer::InflationLayer() : inflation_radius_(0), inscribed_radius_(0), cost_scaling_factor_(0), inflate_unknown_(false), inflate_around_unknown_(false), cell_inflation_radius_(0), cached_cell_inflation_radius_(0), resolution_(0), cache_length_(0), last_min_x_(std::numeric_limits::lowest()), last_min_y_(std::numeric_limits::lowest()), last_max_x_(std::numeric_limits::max()), last_max_y_(std::numeric_limits::max()) { access_ = new mutex_t(); } InflationLayer::~InflationLayer() { dyn_params_handler_.reset(); delete access_; } void InflationLayer::onInitialize() { declareParameter("enabled", rclcpp::ParameterValue(true)); declareParameter("inflation_radius", rclcpp::ParameterValue(0.55)); declareParameter("cost_scaling_factor", rclcpp::ParameterValue(10.0)); declareParameter("inflate_unknown", rclcpp::ParameterValue(false)); declareParameter("inflate_around_unknown", rclcpp::ParameterValue(false)); { auto node = node_.lock(); if (!node) { throw std::runtime_error{"Failed to lock node"}; } node->get_parameter(name_ + "." + "enabled", enabled_); node->get_parameter(name_ + "." + "inflation_radius", inflation_radius_); node->get_parameter(name_ + "." + "cost_scaling_factor", cost_scaling_factor_); node->get_parameter(name_ + "." + "inflate_unknown", inflate_unknown_); node->get_parameter(name_ + "." + "inflate_around_unknown", inflate_around_unknown_); dyn_params_handler_ = node->add_on_set_parameters_callback( std::bind( &InflationLayer::dynamicParametersCallback, this, std::placeholders::_1)); } current_ = true; seen_.clear(); cached_distances_.clear(); cached_costs_.clear(); need_reinflation_ = false; cell_inflation_radius_ = cellDistance(inflation_radius_); matchSize(); } void InflationLayer::matchSize() { std::lock_guard guard(*getMutex()); nav2_costmap_2d::Costmap2D * costmap = layered_costmap_->getCostmap(); resolution_ = costmap->getResolution(); cell_inflation_radius_ = cellDistance(inflation_radius_); computeCaches(); seen_ = std::vector(costmap->getSizeInCellsX() * costmap->getSizeInCellsY(), false); } void InflationLayer::updateBounds( double /*robot_x*/, double /*robot_y*/, double /*robot_yaw*/, double * min_x, double * min_y, double * max_x, double * max_y) { std::lock_guard guard(*getMutex()); if (need_reinflation_) { last_min_x_ = *min_x; last_min_y_ = *min_y; last_max_x_ = *max_x; last_max_y_ = *max_y; *min_x = std::numeric_limits::lowest(); *min_y = std::numeric_limits::lowest(); *max_x = std::numeric_limits::max(); *max_y = std::numeric_limits::max(); need_reinflation_ = false; } else { double tmp_min_x = last_min_x_; double tmp_min_y = last_min_y_; double tmp_max_x = last_max_x_; double tmp_max_y = last_max_y_; last_min_x_ = *min_x; last_min_y_ = *min_y; last_max_x_ = *max_x; last_max_y_ = *max_y; *min_x = std::min(tmp_min_x, *min_x) - inflation_radius_; *min_y = std::min(tmp_min_y, *min_y) - inflation_radius_; *max_x = std::max(tmp_max_x, *max_x) + inflation_radius_; *max_y = std::max(tmp_max_y, *max_y) + inflation_radius_; } } void InflationLayer::onFootprintChanged() { std::lock_guard guard(*getMutex()); inscribed_radius_ = layered_costmap_->getInscribedRadius(); cell_inflation_radius_ = cellDistance(inflation_radius_); computeCaches(); need_reinflation_ = true; if (inflation_radius_ < inscribed_radius_) { RCLCPP_ERROR( logger_, "The configured inflation radius (%.3f) is smaller than " "the computed inscribed radius (%.3f) of your footprint, " "it is highly recommended to set inflation radius to be at " "least as big as the inscribed radius to avoid collisions", inflation_radius_, inscribed_radius_); } RCLCPP_DEBUG( logger_, "InflationLayer::onFootprintChanged(): num footprint points: %zu," " inscribed_radius_ = %.3f, inflation_radius_ = %.3f", layered_costmap_->getFootprint().size(), inscribed_radius_, inflation_radius_); } void InflationLayer::updateCosts( nav2_costmap_2d::Costmap2D & master_grid, int min_i, int min_j, int max_i, int max_j) { std::lock_guard guard(*getMutex()); if (!enabled_ || (cell_inflation_radius_ == 0)) { return; } // make sure the inflation list is empty at the beginning of the cycle (should always be true) for (auto & dist : inflation_cells_) { RCLCPP_FATAL_EXPRESSION( logger_, !dist.empty(), "The inflation list must be empty at the beginning of inflation"); } unsigned char * master_array = master_grid.getCharMap(); unsigned int size_x = master_grid.getSizeInCellsX(), size_y = master_grid.getSizeInCellsY(); if (seen_.size() != size_x * size_y) { RCLCPP_WARN( logger_, "InflationLayer::updateCosts(): seen_ vector size is wrong"); seen_ = std::vector(size_x * size_y, false); } std::fill(begin(seen_), end(seen_), false); // We need to include in the inflation cells outside the bounding // box min_i...max_j, by the amount cell_inflation_radius_. Cells // up to that distance outside the box can still influence the costs // stored in cells inside the box. const int base_min_i = min_i; const int base_min_j = min_j; const int base_max_i = max_i; const int base_max_j = max_j; min_i -= static_cast(cell_inflation_radius_); min_j -= static_cast(cell_inflation_radius_); max_i += static_cast(cell_inflation_radius_); max_j += static_cast(cell_inflation_radius_); min_i = std::max(0, min_i); min_j = std::max(0, min_j); max_i = std::min(static_cast(size_x), max_i); max_j = std::min(static_cast(size_y), max_j); // Inflation list; we append cells to visit in a list associated with // its distance to the nearest obstacle // We use a map to emulate the priority queue used before, // with a notable performance boost // Start with lethal obstacles: by definition distance is 0.0 auto & obs_bin = inflation_cells_[0]; for (int j = min_j; j < max_j; j++) { for (int i = min_i; i < max_i; i++) { int index = static_cast(master_grid.getIndex(i, j)); unsigned char cost = master_array[index]; if (cost == LETHAL_OBSTACLE || (inflate_around_unknown_ && cost == NO_INFORMATION)) { obs_bin.emplace_back(index, i, j, i, j); } } } // Process cells by increasing distance; new cells are appended to the // corresponding distance bin, so they // can overtake previously inserted but farther away cells for (const auto & dist_bin : inflation_cells_) { for (std::size_t i = 0; i < dist_bin.size(); ++i) { // Do not use iterator or for-range based loops to // iterate though dist_bin, since it's size might // change when a new cell is enqueued, invalidating all iterators unsigned int index = dist_bin[i].index_; // ignore if already visited if (seen_[index]) { continue; } seen_[index] = true; unsigned int mx = dist_bin[i].x_; unsigned int my = dist_bin[i].y_; unsigned int sx = dist_bin[i].src_x_; unsigned int sy = dist_bin[i].src_y_; // assign the cost associated with the distance from an obstacle to the cell unsigned char cost = costLookup(mx, my, sx, sy); unsigned char old_cost = master_array[index]; // In order to avoid artifacts appeared out of boundary areas // when some layer is going after inflation_layer, // we need to apply inflation_layer only to inside of given bounds if (static_cast(mx) >= base_min_i && static_cast(my) >= base_min_j && static_cast(mx) < base_max_i && static_cast(my) < base_max_j) { if (old_cost == NO_INFORMATION && (inflate_unknown_ ? (cost > FREE_SPACE) : (cost >= INSCRIBED_INFLATED_OBSTACLE))) { master_array[index] = cost; } else { master_array[index] = std::max(old_cost, cost); } } // attempt to put the neighbors of the current cell onto the inflation list if (mx > 0) { enqueue(index - 1, mx - 1, my, sx, sy); } if (my > 0) { enqueue(index - size_x, mx, my - 1, sx, sy); } if (mx < size_x - 1) { enqueue(index + 1, mx + 1, my, sx, sy); } if (my < size_y - 1) { enqueue(index + size_x, mx, my + 1, sx, sy); } } } for (auto & dist : inflation_cells_) { dist.clear(); dist.reserve(200); } current_ = true; } /** * @brief Given an index of a cell in the costmap, place it into a list pending for obstacle inflation * @param grid The costmap * @param index The index of the cell * @param mx The x coordinate of the cell (can be computed from the index, but saves time to store it) * @param my The y coordinate of the cell (can be computed from the index, but saves time to store it) * @param src_x The x index of the obstacle point inflation started at * @param src_y The y index of the obstacle point inflation started at */ void InflationLayer::enqueue( unsigned int index, unsigned int mx, unsigned int my, unsigned int src_x, unsigned int src_y) { if (!seen_[index]) { // we compute our distance table one cell further than the // inflation radius dictates so we can make the check below double distance = distanceLookup(mx, my, src_x, src_y); // we only want to put the cell in the list if it is within // the inflation radius of the obstacle point if (distance > cell_inflation_radius_) { return; } const unsigned int r = cell_inflation_radius_ + 2; // push the cell data onto the inflation list and mark inflation_cells_[distance_matrix_[mx - src_x + r][my - src_y + r]].emplace_back( index, mx, my, src_x, src_y); } } void InflationLayer::computeCaches() { std::lock_guard guard(*getMutex()); if (cell_inflation_radius_ == 0) { return; } cache_length_ = cell_inflation_radius_ + 2; // based on the inflation radius... compute distance and cost caches if (cell_inflation_radius_ != cached_cell_inflation_radius_) { cached_costs_.resize(cache_length_ * cache_length_); cached_distances_.resize(cache_length_ * cache_length_); for (unsigned int i = 0; i < cache_length_; ++i) { for (unsigned int j = 0; j < cache_length_; ++j) { cached_distances_[i * cache_length_ + j] = hypot(i, j); } } cached_cell_inflation_radius_ = cell_inflation_radius_; } for (unsigned int i = 0; i < cache_length_; ++i) { for (unsigned int j = 0; j < cache_length_; ++j) { cached_costs_[i * cache_length_ + j] = computeCost(cached_distances_[i * cache_length_ + j]); } } int max_dist = generateIntegerDistances(); inflation_cells_.clear(); inflation_cells_.resize(max_dist + 1); for (auto & dist : inflation_cells_) { dist.reserve(200); } } int InflationLayer::generateIntegerDistances() { const int r = cell_inflation_radius_ + 2; const int size = r * 2 + 1; std::vector> points; for (int y = -r; y <= r; y++) { for (int x = -r; x <= r; x++) { if (x * x + y * y <= r * r) { points.emplace_back(x, y); } } } std::sort( points.begin(), points.end(), [](const std::pair & a, const std::pair & b) -> bool { return a.first * a.first + a.second * a.second < b.first * b.first + b.second * b.second; } ); std::vector> distance_matrix(size, std::vector(size, 0)); std::pair last = {0, 0}; int level = 0; for (auto const & p : points) { if (p.first * p.first + p.second * p.second != last.first * last.first + last.second * last.second) { level++; } distance_matrix[p.first + r][p.second + r] = level; last = p; } distance_matrix_ = distance_matrix; return level; } /** * @brief Callback executed when a parameter change is detected * @param event ParameterEvent message */ rcl_interfaces::msg::SetParametersResult InflationLayer::dynamicParametersCallback( std::vector parameters) { std::lock_guard guard(*getMutex()); rcl_interfaces::msg::SetParametersResult result; bool need_cache_recompute = false; for (auto parameter : parameters) { const auto & param_type = parameter.get_type(); const auto & param_name = parameter.get_name(); if (param_type == ParameterType::PARAMETER_DOUBLE) { if (param_name == name_ + "." + "inflation_radius" && inflation_radius_ != parameter.as_double()) { inflation_radius_ = parameter.as_double(); need_reinflation_ = true; need_cache_recompute = true; } else if (param_name == name_ + "." + "cost_scaling_factor" && // NOLINT cost_scaling_factor_ != parameter.as_double()) { cost_scaling_factor_ = parameter.as_double(); need_reinflation_ = true; need_cache_recompute = true; } } else if (param_type == ParameterType::PARAMETER_BOOL) { if (param_name == name_ + "." + "enabled" && enabled_ != parameter.as_bool()) { enabled_ = parameter.as_bool(); need_reinflation_ = true; current_ = false; } else if (param_name == name_ + "." + "inflate_unknown" && // NOLINT inflate_unknown_ != parameter.as_bool()) { inflate_unknown_ = parameter.as_bool(); need_reinflation_ = true; } else if (param_name == name_ + "." + "inflate_around_unknown" && // NOLINT inflate_around_unknown_ != parameter.as_bool()) { inflate_around_unknown_ = parameter.as_bool(); need_reinflation_ = true; } } } if (need_cache_recompute) { matchSize(); } result.successful = true; return result; } } // namespace nav2_costmap_2d