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_