LazyLBTRRT.h

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/* Author: Oren Salzman, Mark Moll */
 
#ifndef OMPL_CONTRIB_LAZY_LBTRRT_
#define OMPL_CONTRIB_LAZY_LBTRRT_
 
#include "ompl/geometric/planners/PlannerIncludes.h"
#include "ompl/datastructures/NearestNeighbors.h"
#include "ompl/base/goals/GoalSampleableRegion.h"
#include "ompl/datastructures/LPAstarOnGraph.h"
 
#include <fstream>
#include <vector>
#include <tuple>
#include <cassert>
 
#include <boost/graph/graph_traits.hpp>
#include <boost/graph/adjacency_list.hpp>
 
namespace ompl
{
    namespace geometric
    {
        class LazyLBTRRT : public base::Planner
        {
        public:
            LazyLBTRRT(const base::SpaceInformationPtr &si);
 
            ~LazyLBTRRT() override;
 
            void getPlannerData(base::PlannerData &data) const override;
 
            base::PlannerStatus solve(const base::PlannerTerminationCondition &ptc) override;
 
            void clear() override;
 
            void setGoalBias(double goalBias)
            {
                goalBias_ = goalBias;
            }
 
            double getGoalBias() const
            {
                return goalBias_;
            }
 
            void setRange(double distance)
            {
                maxDistance_ = distance;
            }
 
            double getRange() const
            {
                return maxDistance_;
            }
 
            template <template <typename T> class NN>
            void setNearestNeighbors()
            {
                if (nn_ && nn_->size() != 0)
                    OMPL_WARN("Calling setNearestNeighbors will clear all states.");
                clear();
                nn_ = std::make_shared<NN<Motion *>>();
                setup();
            }
 
            void setup() override;
 
            void setApproximationFactor(double epsilon)
            {
                epsilon_ = epsilon;
            }
 
            // Planner progress property functions
            std::string getIterationCount() const
            {
                return std::to_string(iterations_);
            }
            std::string getBestCost() const
            {
                return std::to_string(bestCost_);
            }
 
        protected:
            class Motion
            {
            public:
                Motion() = default;
 
                Motion(const base::SpaceInformationPtr &si) : state_(si->allocState())
                {
                }
 
                ~Motion() = default;
 
                std::size_t id_;
 
                base::State *state_{nullptr};
            };
 
            using WeightProperty = boost::property<boost::edge_weight_t, double>;
            using BoostGraph = boost::adjacency_list<boost::vecS,         // container type for the out edge list
                                                     boost::vecS,         // container type for the vertex list
                                                     boost::undirectedS,  // directedS / undirectedS / bidirectionalS.
                                                     std::size_t,         // vertex properties
                                                     WeightProperty       // edge properties
                                                     >;
 
            friend class CostEstimatorApx;  // allow CostEstimatorApx access to private members
            class CostEstimatorApx
            {
            public:
                CostEstimatorApx(LazyLBTRRT *alg) : alg_(alg)
                {
                }
                double operator()(std::size_t i)
                {
                    double lb_estimate = (*(alg_->LPAstarLb_))(i);
                    if (lb_estimate != std::numeric_limits<double>::infinity())
                        return lb_estimate;
 
                    return alg_->distanceFunction(alg_->idToMotionMap_[i], alg_->startMotion_);
                }
 
            private:
                LazyLBTRRT *alg_;
            };  // CostEstimatorApx
 
            class CostEstimatorLb
            {
            public:
                CostEstimatorLb(base::Goal *goal, std::vector<Motion *> &idToMotionMap)
                  : goal_(goal), idToMotionMap_(idToMotionMap)
                {
                }
                double operator()(std::size_t i)
                {
                    double dist = 0.0;
                    goal_->isSatisfied(idToMotionMap_[i]->state_, &dist);
 
                    return dist;
                }
 
            private:
                base::Goal *goal_;
                std::vector<Motion *> &idToMotionMap_;
            };  // CostEstimatorLb
 
            using LPAstarApx = LPAstarOnGraph<BoostGraph, CostEstimatorApx>;
            using LPAstarLb = LPAstarOnGraph<BoostGraph, CostEstimatorLb>;
 
            void sampleBiased(const base::GoalSampleableRegion *goal_s, base::State *rstate);
 
            void freeMemory();
 
            double distanceFunction(const base::State *a, const base::State *b) const
            {
                return si_->distance(a, b);
            }
            double distanceFunction(const Motion *a, const Motion *b) const
            {
                return si_->distance(a->state_, b->state_);
            }
            bool checkMotion(const base::State *a, const base::State *b) const
            {
                return si_->checkMotion(a, b);
            }
            bool checkMotion(const Motion *a, const Motion *b) const
            {
                return si_->checkMotion(a->state_, b->state_);
            }
 
            Motion *getMotion(std::size_t id) const
            {
                assert(idToMotionMap_.size() > id);
                return idToMotionMap_[id];
            }
            void addVertex(const Motion *a)
            {
                boost::add_vertex(a->id_, graphApx_);
                boost::add_vertex(a->id_, graphLb_);
            }
 
            void addEdgeApx(Motion *a, Motion *b, double c)
            {
                WeightProperty w(c);
                boost::add_edge(a->id_, b->id_, w, graphApx_);
                LPAstarApx_->insertEdge(a->id_, b->id_, c);
                LPAstarApx_->insertEdge(b->id_, a->id_, c);
            }
            void addEdgeLb(const Motion *a, const Motion *b, double c)
            {
                WeightProperty w(c);
                boost::add_edge(a->id_, b->id_, w, graphLb_);
                LPAstarLb_->insertEdge(a->id_, b->id_, c);
                LPAstarLb_->insertEdge(b->id_, a->id_, c);
            }
            bool edgeExistsApx(std::size_t a, std::size_t b)
            {
                return boost::edge(a, b, graphApx_).second;
            }
            bool edgeExistsApx(const Motion *a, const Motion *b)
            {
                return edgeExistsApx(a->id_, b->id_);
            }
            bool edgeExistsLb(const Motion *a, const Motion *b)
            {
                return boost::edge(a->id_, b->id_, graphLb_).second;
            }
            void removeEdgeLb(const Motion *a, const Motion *b)
            {
                boost::remove_edge(a->id_, b->id_, graphLb_);
                LPAstarLb_->removeEdge(a->id_, b->id_);
                LPAstarLb_->removeEdge(b->id_, a->id_);
            }
            std::tuple<Motion *, base::State *, double> rrtExtend(const base::GoalSampleableRegion *goal_s,
                                                                  base::State *xstate, Motion *rmotion,
                                                                  double &approxdif);
            void rrt(const base::PlannerTerminationCondition &ptc, base::GoalSampleableRegion *goal_s,
                     base::State *xstate, Motion *rmotion, double &approxdif);
            Motion *createMotion(const base::GoalSampleableRegion *goal_s, const base::State *st);
            Motion *createGoalMotion(const base::GoalSampleableRegion *goal_s);
 
            void closeBounds(const base::PlannerTerminationCondition &ptc);
 
            double getApproximationFactor() const
            {
                return epsilon_;
            }
 
            base::StateSamplerPtr sampler_;
 
            std::shared_ptr<NearestNeighbors<Motion *>> nn_;
 
            double goalBias_{0.05};
 
            double maxDistance_{0.};
 
            RNG rng_;
 
            double epsilon_{.4};
 
            Motion *lastGoalMotion_{nullptr};
 
            BoostGraph graphLb_;
            BoostGraph graphApx_;
            Motion *startMotion_;
            Motion *goalMotion_{nullptr};  // root of LPAstarApx_
            LPAstarApx *LPAstarApx_{nullptr};  // rooted at target
            LPAstarLb *LPAstarLb_{nullptr};  // rooted at source
            std::vector<Motion *> idToMotionMap_;
 
            // Planner progress properties
            unsigned int iterations_{0};
            double bestCost_;
        };
    }
}
 
#endif  // OMPL_CONTRIB_LAZY_LBTRRT_