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tutorial_demo_node.cpp
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tutorial_demo_node.cpp
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#include <ros/ros.h>
#include <grid_map/grid_map.hpp>
#include <vector>
#include <string>
#include <cmath>
#include <limits>
using namespace grid_map;
int main(int argc, char** argv)
{
// Initialize node and publisher.
ros::init(argc, argv, "grid_map_tutorial_demo");
ros::NodeHandle nh("~");
ros::Publisher publisher = nh.advertise<grid_map_msgs::GridMap>("grid_map", 1, true);
// Create grid map.
GridMap map({"elevation", "normal_x", "normal_y", "normal_z"});
map.setFrameId("map");
map.setGeometry(Length(1.2, 2.0), 0.03, Position(0.0, -0.1));
ROS_INFO("Created map with size %f x %f m (%i x %i cells).\n The center of the map is located at (%f, %f) in the %s frame.",
map.getLength().x(), map.getLength().y(),
map.getSize()(0), map.getSize()(1),
map.getPosition().x(), map.getPosition().y(), map.getFrameId().c_str());
// Work with grid map in a loop.
ros::Rate rate(30.0);
while (nh.ok()) {
ros::Time time = ros::Time::now();
// Add elevation and surface normal (iterating through grid map and adding data).
for (GridMapIterator it(map); !it.isPastEnd(); ++it) {
Position position;
map.getPosition(*it, position);
map.at("elevation", *it) = -0.04 + 0.2 * std::sin(3.0 * time.toSec() + 5.0 * position.y()) * position.x();
Eigen::Vector3d normal(-0.2 * std::sin(3.0 * time.toSec() + 5.0 * position.y()),
-position.x() * std::cos(3.0 * time.toSec() + 5.0 * position.y()), 1.0);
normal.normalize();
map.at("normal_x", *it) = normal.x();
map.at("normal_y", *it) = normal.y();
map.at("normal_z", *it) = normal.z();
}
// Add noise (using Eigen operators).
map.add("noise", 0.015 * Matrix::Random(map.getSize()(0), map.getSize()(1)));
map.add("elevation_noisy", map.get("elevation") + map["noise"]);
// Adding outliers (accessing cell by position).
for (unsigned int i = 0; i < 500; ++i) {
Position randomPosition = Position::Random();
if (map.isInside(randomPosition))
map.atPosition("elevation_noisy", randomPosition) = std::numeric_limits<float>::infinity();
}
// Filter values for submap (iterators).
map.add("elevation_filtered", map.get("elevation_noisy"));
Position topLeftCorner(1.0, 0.4);
limitPositionToRange(topLeftCorner, map.getLength(), map.getPosition());
Index startIndex;
map.getIndex(topLeftCorner, startIndex);
ROS_INFO_ONCE("Top left corner was limited from (1.0, 0.2) to (%f, %f) and corresponds to index (%i, %i).",
topLeftCorner.x(), topLeftCorner.y(), startIndex(0), startIndex(1));
Size size = (Length(1.2, 0.8) / map.getResolution()).cast<int>();
SubmapIterator it(map, startIndex, size);
for (; !it.isPastEnd(); ++it) {
Position currentPosition;
map.getPosition(*it, currentPosition);
double radius = 0.1;
double mean = 0.0;
double sumOfWeights = 0.0;
// Compute weighted mean.
for (CircleIterator circleIt(map, currentPosition, radius);
!circleIt.isPastEnd(); ++circleIt) {
if (!map.isValid(*circleIt, "elevation_noisy")) continue;
Position currentPositionInCircle;
map.getPosition(*circleIt, currentPositionInCircle);
// Computed weighted mean based on Euclidian distance.
double distance = (currentPosition - currentPositionInCircle).norm();
double weight = pow(radius - distance, 2);
mean += weight * map.at("elevation_noisy", *circleIt);
sumOfWeights += weight;
}
map.at("elevation_filtered", *it) = mean / sumOfWeights;
}
// Show absolute difference and compute mean squared error.
map.add("error", (map.get("elevation_filtered") - map.get("elevation")).cwiseAbs());
unsigned int nCells = map.getSize().prod();
double rootMeanSquaredError = sqrt((map["error"].array().pow(2).sum()) / nCells);
// Publish grid map.
map.setTimestamp(time.toSec());
grid_map_msgs::GridMap message;
GridMapRosConverter::toMessage(map, message);
publisher.publish(message);
ROS_INFO_THROTTLE(1.0, "Grid map (timestamp %f) published.", message.info.header.stamp.toSec());
rate.sleep();
}
return 0;
}