moveit2
The MoveIt Motion Planning Framework for ROS 2.
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GreedyKCenters.h
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34
35/* Author: Mark Moll */
36
37// This file is a slightly modified version of <ompl/datastructures/GreedyKCenters.h>
38
39#pragma once
40
41#include <functional>
42#include <random>
43#include <eigen3/Eigen/Core>
44
46{
50template <typename _T>
52{
53public:
55 using DistanceFunction = std::function<double(const _T&, const _T&)>;
57 using Matrix = Eigen::MatrixXd;
58
59 GreedyKCenters() = default;
60 GreedyKCenters(const GreedyKCenters&) = default;
61 GreedyKCenters(GreedyKCenters&&) noexcept = default;
62 GreedyKCenters& operator=(const GreedyKCenters&) = default;
63 GreedyKCenters& operator=(GreedyKCenters&&) noexcept = default;
64 virtual ~GreedyKCenters() = default;
65
68 {
69 distFun_ = distFun;
70 }
71
74 {
75 return distFun_;
76 }
77
86 void kcenters(const std::vector<_T>& data, unsigned int k, std::vector<unsigned int>& centers, Matrix& dists)
87 {
88 // array containing the minimum distance between each data point
89 // and the centers computed so far
90 std::vector<double> min_dist(data.size(), std::numeric_limits<double>::infinity());
91
92 centers.clear();
93 centers.reserve(k);
94 if (static_cast<long unsigned int>(dists.rows()) < data.size() || static_cast<long unsigned int>(dists.cols()) < k)
95 dists.resize(std::max(2 * static_cast<long unsigned int>(dists.rows()) + 1, data.size()), k);
96 // first center is picked randomly
97 centers.push_back(std::uniform_int_distribution<size_t>{ 0, data.size() - 1 }(rsl::rng()));
98 for (unsigned i = 1; i < k; ++i)
99 {
100 unsigned ind = 0;
101 const _T& center = data[centers[i - 1]];
102 double max_dist = -std::numeric_limits<double>::infinity();
103 for (unsigned j = 0; j < data.size(); ++j)
104 {
105 if ((dists(j, i - 1) = distFun_(data[j], center)) < min_dist[j])
106 min_dist[j] = dists(j, i - 1);
107 // the j-th center is the one furthest away from center 0,..,j-1
108 if (min_dist[j] > max_dist)
109 {
110 ind = j;
111 max_dist = min_dist[j];
112 }
113 }
114 // no more centers available
115 if (max_dist < std::numeric_limits<double>::epsilon())
116 break;
117 centers.push_back(ind);
118 }
119
120 const _T& center = data[centers.back()];
121 unsigned i = centers.size() - 1;
122 for (unsigned j = 0; j < data.size(); ++j)
123 dists(j, i) = distFun_(data[j], center);
124 }
125
126protected:
129};
130} // namespace cached_ik_kinematics_plugin
An instance of this class can be used to greedily select a given number of representatives from a set...
GreedyKCenters(const GreedyKCenters &)=default
void kcenters(const std::vector< _T > &data, unsigned int k, std::vector< unsigned int > &centers, Matrix &dists)
Greedy algorithm for selecting k centers.
void setDistanceFunction(const DistanceFunction &distFun)
Set the distance function to use.
Eigen::MatrixXd Matrix
A matrix type for storing distances between points and centers.
std::function< double(const _T &, const _T &)> DistanceFunction
The definition of a distance function.
DistanceFunction distFun_
The used distance function.
GreedyKCenters(GreedyKCenters &&) noexcept=default
const DistanceFunction & getDistanceFunction() const
Get the distance function used.