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agv_pro_ros2/navigation2/nav2_costmap_2d/plugins/inflation_layer.cpp
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2025-05-27 19:03:40 +08:00

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/*********************************************************************
*
* Software License Agreement (BSD License)
*
* Copyright (c) 2008, 2013, Willow Garage, Inc.
* All rights reserved.
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* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* Author: Eitan Marder-Eppstein
* David V. Lu!!
*********************************************************************/
#include "nav2_costmap_2d/inflation_layer.hpp"
#include <limits>
#include <map>
#include <vector>
#include <algorithm>
#include <utility>
#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<double>::lowest()),
last_min_y_(std::numeric_limits<double>::lowest()),
last_max_x_(std::numeric_limits<double>::max()),
last_max_y_(std::numeric_limits<double>::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<Costmap2D::mutex_t> guard(*getMutex());
nav2_costmap_2d::Costmap2D * costmap = layered_costmap_->getCostmap();
resolution_ = costmap->getResolution();
cell_inflation_radius_ = cellDistance(inflation_radius_);
computeCaches();
seen_ = std::vector<bool>(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<Costmap2D::mutex_t> 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<double>::lowest();
*min_y = std::numeric_limits<double>::lowest();
*max_x = std::numeric_limits<double>::max();
*max_y = std::numeric_limits<double>::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<Costmap2D::mutex_t> 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<Costmap2D::mutex_t> 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<bool>(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<int>(cell_inflation_radius_);
min_j -= static_cast<int>(cell_inflation_radius_);
max_i += static_cast<int>(cell_inflation_radius_);
max_j += static_cast<int>(cell_inflation_radius_);
min_i = std::max(0, min_i);
min_j = std::max(0, min_j);
max_i = std::min(static_cast<int>(size_x), max_i);
max_j = std::min(static_cast<int>(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<distance, list> 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<int>(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<int>(mx) >= base_min_i &&
static_cast<int>(my) >= base_min_j &&
static_cast<int>(mx) < base_max_i &&
static_cast<int>(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<Costmap2D::mutex_t> 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<std::pair<int, int>> 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<int, int> & a, const std::pair<int, int> & b) -> bool {
return a.first * a.first + a.second * a.second < b.first * b.first + b.second * b.second;
}
);
std::vector<std::vector<int>> distance_matrix(size, std::vector<int>(size, 0));
std::pair<int, int> 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<rclcpp::Parameter> parameters)
{
std::lock_guard<Costmap2D::mutex_t> 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