Program Listing for File FMT.h
↰ Return to documentation for file (src/ompl/geometric/planners/fmt/FMT.h)
/*********************************************************************
* Software License Agreement (BSD License)
*
* Copyright (c) 2013, Autonomous Systems Laboratory, Stanford University
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of Stanford University nor the names of its
* 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
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*********************************************************************/
/* Authors: Ashley Clark (Stanford) and Wolfgang Pointner (AIT) */
/* Co-developers: Brice Rebsamen (Stanford), Tim Wheeler (Stanford)
Edward Schmerling (Stanford), and Javier V. Gómez (UC3M - Stanford)*/
/* Algorithm design: Lucas Janson (Stanford) and Marco Pavone (Stanford) */
/* Acknowledgements for insightful comments: Oren Salzman (Tel Aviv University),
* Joseph Starek (Stanford) */
#ifndef OMPL_GEOMETRIC_PLANNERS_FMT_
#define OMPL_GEOMETRIC_PLANNERS_FMT_
#include <ompl/geometric/planners/PlannerIncludes.h>
#include <ompl/base/goals/GoalSampleableRegion.h>
#include <ompl/datastructures/NearestNeighbors.h>
#include <ompl/datastructures/BinaryHeap.h>
#include <ompl/base/OptimizationObjective.h>
#include <map>
namespace ompl
{
namespace geometric
{
class FMT : public ompl::base::Planner
{
public:
FMT(const base::SpaceInformationPtr &si);
~FMT() override;
void setup() override;
base::PlannerStatus solve(const base::PlannerTerminationCondition &ptc) override;
void clear() override;
void getPlannerData(base::PlannerData &data) const override;
void setNumSamples(const unsigned int numSamples)
{
numSamples_ = numSamples;
}
unsigned int getNumSamples() const
{
return numSamples_;
}
void setNearestK(bool nearestK)
{
nearestK_ = nearestK;
}
bool getNearestK() const
{
return nearestK_;
}
void setRadiusMultiplier(const double radiusMultiplier)
{
if (radiusMultiplier <= 0.0)
throw Exception("Radius multiplier must be greater than zero");
radiusMultiplier_ = radiusMultiplier;
}
double getRadiusMultiplier() const
{
return radiusMultiplier_;
}
void setFreeSpaceVolume(const double freeSpaceVolume)
{
if (freeSpaceVolume < 0.0)
throw Exception("Free space volume should be greater than zero");
freeSpaceVolume_ = freeSpaceVolume;
}
double getFreeSpaceVolume() const
{
return freeSpaceVolume_;
}
void setCacheCC(bool ccc)
{
cacheCC_ = ccc;
}
bool getCacheCC() const
{
return cacheCC_;
}
void setHeuristics(bool h)
{
heuristics_ = h;
}
bool getHeuristics() const
{
return heuristics_;
}
void setExtendedFMT(bool e)
{
extendedFMT_ = e;
}
bool getExtendedFMT() const
{
return extendedFMT_;
}
protected:
class Motion
{
public:
enum SetType
{
SET_CLOSED,
SET_OPEN,
SET_UNVISITED
};
Motion() = default;
Motion(const base::SpaceInformationPtr &si)
: state_(si->allocState())
{
}
~Motion() = default;
void setState(base::State *state)
{
state_ = state;
}
base::State *getState() const
{
return state_;
}
void setParent(Motion *parent)
{
parent_ = parent;
}
Motion *getParent() const
{
return parent_;
}
void setCost(const base::Cost cost)
{
cost_ = cost;
}
base::Cost getCost() const
{
return cost_;
}
void setSetType(const SetType currentSet)
{
currentSet_ = currentSet;
}
SetType getSetType() const
{
return currentSet_;
}
bool alreadyCC(Motion *m)
{
return !(collChecksDone_.find(m) == collChecksDone_.end());
}
void addCC(Motion *m)
{
collChecksDone_.insert(m);
}
void setHeuristicCost(const base::Cost h)
{
hcost_ = h;
}
base::Cost getHeuristicCost() const
{
return hcost_;
}
std::vector<Motion *> &getChildren()
{
return children_;
}
protected:
base::State *state_{nullptr};
Motion *parent_{nullptr};
base::Cost cost_{0.};
base::Cost hcost_{0.};
SetType currentSet_{SET_UNVISITED};
std::set<Motion *> collChecksDone_;
std::vector<Motion *> children_;
};
struct MotionCompare
{
MotionCompare() = default;
/* Returns true if m1 is lower cost than m2. m1 and m2 must
have been instantiated with the same optimization objective */
bool operator()(const Motion *m1, const Motion *m2) const
{
if (heuristics_)
return opt_->isCostBetterThan(opt_->combineCosts(m1->getCost(), m1->getHeuristicCost()),
opt_->combineCosts(m2->getCost(), m2->getHeuristicCost()));
return opt_->isCostBetterThan(m1->getCost(), m2->getCost());
}
base::OptimizationObjective *opt_{nullptr};
bool heuristics_{false};
};
double distanceFunction(const Motion *a, const Motion *b) const
{
return opt_->motionCost(a->getState(), b->getState()).value();
}
void freeMemory();
void sampleFree(const ompl::base::PlannerTerminationCondition &ptc);
void assureGoalIsSampled(const ompl::base::GoalSampleableRegion *goal);
double calculateUnitBallVolume(unsigned int dimension) const;
double calculateRadius(unsigned int dimension, unsigned int n) const;
void saveNeighborhood(Motion *m);
void traceSolutionPathThroughTree(Motion *goalMotion);
bool expandTreeFromNode(Motion **z);
void updateNeighborhood(Motion *m, std::vector<Motion *> nbh);
Motion *getBestParent(Motion *m, std::vector<Motion *> &neighbors, base::Cost &cMin);
using MotionBinHeap = ompl::BinaryHeap<Motion *, MotionCompare>;
MotionBinHeap Open_;
std::map<Motion *, std::vector<Motion *>> neighborhoods_;
unsigned int numSamples_{1000u};
unsigned int collisionChecks_{0u};
bool nearestK_{true};
bool cacheCC_{true};
bool heuristics_{false};
double NNr_;
unsigned int NNk_;
double freeSpaceVolume_;
double radiusMultiplier_{1.1};
std::shared_ptr<NearestNeighbors<Motion *>> nn_;
base::StateSamplerPtr sampler_;
base::OptimizationObjectivePtr opt_;
Motion *lastGoalMotion_;
base::State *goalState_;
bool extendedFMT_{true};
// For sorting a list of costs and getting only their sorted indices
struct CostIndexCompare
{
CostIndexCompare(const std::vector<base::Cost> &costs, const base::OptimizationObjective &opt)
: costs_(costs), opt_(opt)
{
}
bool operator()(unsigned i, unsigned j)
{
return opt_.isCostBetterThan(costs_[i], costs_[j]);
}
const std::vector<base::Cost> &costs_;
const base::OptimizationObjective &opt_;
};
};
}
}
#endif // OMPL_GEOMETRIC_PLANNERS_FMT_