OrderedInfSampler.cpp
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34 
35 /* Authors: Jonathan Gammell */
36 
37 #include "ompl/base/samplers/informed/OrderedInfSampler.h"
38 #include "ompl/base/OptimizationObjective.h"
39 
40 namespace ompl
41 {
42  namespace base
43  {
44  // The default rejection-sampling class:
45  OrderedInfSampler::OrderedInfSampler(const InformedSamplerPtr &infSamplerPtr, unsigned int batchSize)
46  : InformedSampler(infSamplerPtr->getProblemDefn(), infSamplerPtr->getMaxNumberOfIters())
47  , infSampler_(infSamplerPtr)
48  , batchSize_(batchSize)
49  , orderedSamples_([this](const State *lhs, const State *rhs)
50  {
51  return queueComparator(lhs, rhs);
52  })
53  {
54  }
55 
56  bool OrderedInfSampler::sampleUniform(State *statePtr, const Cost &maxCost)
57  {
58  // Variables
59  // Whether a sampler has been found and returned
60  bool found = false;
61 
62  // Repeat until a valid pointer is found
63  while (!found)
64  {
65  // Check if the batch is empty
66  if (orderedSamples_.empty())
67  {
68  // It is, recreate:
69  createBatch(maxCost);
70  }
71 
72  // Does the front of the priority queue meet our requirement (as the requirement may have changed since
73  // the batch was generated)
74  if (InformedSampler::opt_->isCostBetterThan(InformedSampler::heuristicSolnCost(orderedSamples_.top()),
75  maxCost))
76  {
77  // Copy the front of the priority queue.
78  InformedSampler::space_->copyState(statePtr, orderedSamples_.top());
79 
80  // Free the pointer in the queue
81  InformedSampler::space_->freeState(orderedSamples_.top());
82 
83  // Pop it
84  orderedSamples_.pop();
85 
86  // And mark that we've found a sample
87  found = true;
88  }
89  else
90  {
91  // It does not, clear the queue
92  clearBatch();
93  }
94  }
95 
96  return found;
97  }
98 
99  bool OrderedInfSampler::sampleUniform(State *, const Cost &, const Cost &)
100  {
101  throw ompl::Exception("Not implemented");
102 
103  return false;
104  }
105 
107  {
108  return infSampler_->hasInformedMeasure();
109  }
110 
111  double OrderedInfSampler::getInformedMeasure(const Cost &currentCost) const
112  {
113  return infSampler_->getInformedMeasure(currentCost);
114  }
115 
116  bool OrderedInfSampler::queueComparator(const State *a, const State *b)
117  {
118  return InformedSampler::opt_->isCostBetterThan(InformedSampler::heuristicSolnCost(b),
120  }
121 
122  void OrderedInfSampler::createBatch(const Cost &maxCost)
123  {
124  // Allocate, create and store batchSize_ samples
125  for (unsigned int i = 0u; i < batchSize_; ++i)
126  {
127  // Allocate a state pointer
128  State *newStatePtr = InformedSampler::space_->allocState();
129 
130  // Sample the state pointer using the wrapped sampler
131  infSampler_->sampleUniform(newStatePtr, maxCost);
132 
133  // Store it into the queue
134  orderedSamples_.push(newStatePtr);
135  }
136  }
137 
138  void OrderedInfSampler::createBatch(const Cost &, const Cost &)
139  {
140  throw ompl::Exception("Not implemented");
141  }
142 
143  void OrderedInfSampler::clearBatch()
144  {
145  // Iterate through the entire queue, removing the element and freeing it.
146  while (!orderedSamples_.empty())
147  {
148  // Free the front state
149  InformedSampler::space_->freeState(orderedSamples_.top());
150 
151  // Pop the front state
152  orderedSamples_.pop();
153  }
154  }
155  }; // base
156 }; // ompl
Definition of an abstract state.
Definition: State.h:50
bool hasInformedMeasure() const override
Whether the wrapped sampler can provide a measure of the informed subset.
double getInformedMeasure(const Cost &currentCost) const override
The measure of the subset of the state space defined by the current solution cost that is being searc...
Definition of a cost value. Can represent the cost of a motion or the cost of a state.
Definition: Cost.h:48
OrderedInfSampler(const InformedSamplerPtr &infSamplerPtr, unsigned int batchSize)
Construct an ordering wrapper around the provided informed sampler.
OptimizationObjectivePtr opt_
A copy of the optimization objective.
bool sampleUniform(State *statePtr, const Cost &maxCost) override
Sample uniformly in the subset of the state space whose heuristic solution estimates are less than th...
An abstract class for the concept of using information about the state space and the current solution...
virtual Cost heuristicSolnCost(const State *statePtr) const
A helper function to calculate the heuristic estimate of the solution cost for a given state using th...
StateSpacePtr space_
A copy of the state space.
The exception type for ompl.
Definition: Exception.h:47
Main namespace. Contains everything in this library.
Definition: AppBase.h:22