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  /* Author: Ioan Sucan */
  
  #include "ompl/geometric/planners/rrt/pRRT.h"
  #include "ompl/base/goals/GoalSampleableRegion.h"
  #include "ompl/tools/config/SelfConfig.h"
  #include <limits>
  
  ompl::geometric::pRRT::pRRT(const base::SpaceInformationPtr &si) : base::Planner(si, "pRRT"), samplerArray_(si)
  {
      specs_.approximateSolutions = true;
      specs_.multithreaded = true;
      specs_.directed = true;
  
      setThreadCount(2);
  
      Planner::declareParam<double>("range", this, &pRRT::setRange, &pRRT::getRange, "0.:1.:10000.");
      Planner::declareParam<double>("goal_bias", this, &pRRT::setGoalBias, &pRRT::getGoalBias, "0.:.05:1.");
      Planner::declareParam<unsigned int>("thread_count", this, &pRRT::setThreadCount, &pRRT::getThreadCount, "1:64");
  }
  
  ompl::geometric::pRRT::~pRRT()
  {
      freeMemory();
  }
  
  void ompl::geometric::pRRT::setup()
  {
      Planner::setup();
      tools::SelfConfig sc(si_, getName());
      sc.configurePlannerRange(maxDistance_);
  
      if (!nn_)
          nn_.reset(tools::SelfConfig::getDefaultNearestNeighbors<Motion *>(this));
      nn_->setDistanceFunction([this](const Motion *a, const Motion *b)
                               {
                                   return distanceFunction(a, b);
                               });
  }
  
  void ompl::geometric::pRRT::clear()
  {
      Planner::clear();
      samplerArray_.clear();
      freeMemory();
      if (nn_)
          nn_->clear();
      lastGoalMotion_ = nullptr;
  }
  
  void ompl::geometric::pRRT::freeMemory()
  {
      if (nn_)
      {
          std::vector<Motion *> motions;
          nn_->list(motions);
          for (auto &motion : motions)
          {
              if (motion->state)
                  si_->freeState(motion->state);
              delete motion;
          }
      }
  }
  
  void ompl::geometric::pRRT::threadSolve(unsigned int tid, const base::PlannerTerminationCondition &ptc,
                                          SolutionInfo *sol)
  {
      base::Goal *goal = pdef_->getGoal().get();
      auto *goal_s = dynamic_cast<base::GoalSampleableRegion *>(goal);
      RNG rng;
  
      auto *rmotion = new Motion(si_);
      base::State *rstate = rmotion->state;
      base::State *xstate = si_->allocState();
  
      while (sol->solution == nullptr && ptc == false)
      {
          /* sample random state (with goal biasing) */
          if (goal_s && rng.uniform01() < goalBias_ && goal_s->canSample())
              goal_s->sampleGoal(rstate);
          else
              samplerArray_[tid]->sampleUniform(rstate);
  
          /* find closest state in the tree */
          nnLock_.lock();
          Motion *nmotion = nn_->nearest(rmotion);
          nnLock_.unlock();
          base::State *dstate = rstate;
  
          /* find state to add */
          double d = si_->distance(nmotion->state, rstate);
          if (d > maxDistance_)
          {
              si_->getStateSpace()->interpolate(nmotion->state, rstate, maxDistance_ / d, xstate);
              dstate = xstate;
          }
  
          if (si_->checkMotion(nmotion->state, dstate))
          {
              /* create a motion */
              auto *motion = new Motion(si_);
              si_->copyState(motion->state, dstate);
              motion->parent = nmotion;
  
              nnLock_.lock();
              nn_->add(motion);
              nnLock_.unlock();
  
              double dist = 0.0;
              bool solved = goal->isSatisfied(motion->state, &dist);
              if (solved)
              {
                  sol->lock.lock();
                  sol->approxdif = dist;
                  sol->solution = motion;
                  sol->lock.unlock();
                  break;
              }
              if (dist < sol->approxdif)
              {
                  sol->lock.lock();
                  if (dist < sol->approxdif)
                  {
                      sol->approxdif = dist;
                      sol->approxsol = motion;
                  }
                  sol->lock.unlock();
              }
          }
      }
  
      si_->freeState(xstate);
      if (rmotion->state)
          si_->freeState(rmotion->state);
      delete rmotion;
  }
  
  ompl::base::PlannerStatus ompl::geometric::pRRT::solve(const base::PlannerTerminationCondition &ptc)
  {
      checkValidity();
  
      auto *goal = dynamic_cast<base::GoalRegion *>(pdef_->getGoal().get());
  
      if (!goal)
      {
          OMPL_ERROR("%s: Unknown type of goal", getName().c_str());
          return base::PlannerStatus::UNRECOGNIZED_GOAL_TYPE;
      }
  
      samplerArray_.resize(threadCount_);
  
      while (const base::State *st = pis_.nextStart())
      {
          auto *motion = new Motion(si_);
          si_->copyState(motion->state, st);
          nn_->add(motion);
      }
  
      if (nn_->size() == 0)
      {
          OMPL_ERROR("%s: There are no valid initial states!", getName().c_str());
          return base::PlannerStatus::INVALID_START;
      }
  
      OMPL_INFORM("%s: Starting planning with %u states already in datastructure", getName().c_str(), nn_->size());
  
      SolutionInfo sol;
      sol.solution = nullptr;
      sol.approxsol = nullptr;
      sol.approxdif = std::numeric_limits<double>::infinity();
  
      std::vector<std::thread *> th(threadCount_);
      for (unsigned int i = 0; i < threadCount_; ++i)
          th[i] = new std::thread([this, i, &ptc, &sol]
                                  {
                                      return threadSolve(i, ptc, &sol);
                                  });
      for (unsigned int i = 0; i < threadCount_; ++i)
      {
          th[i]->join();
          delete th[i];
      }
  
      bool solved = false;
      bool approximate = false;
      if (sol.solution == nullptr)
      {
          sol.solution = sol.approxsol;
          approximate = true;
      }
  
      if (sol.solution != nullptr)
      {
          lastGoalMotion_ = sol.solution;
  
          /* construct the solution path */
          std::vector<Motion *> mpath;
          while (sol.solution != nullptr)
          {
              mpath.push_back(sol.solution);
              sol.solution = sol.solution->parent;
          }
  
          /* set the solution path */
          auto path(std::make_shared<PathGeometric>(si_));
          for (int i = mpath.size() - 1; i >= 0; --i)
              path->append(mpath[i]->state);
  
          pdef_->addSolutionPath(path, approximate, sol.approxdif, getName());
          solved = true;
      }
  
      OMPL_INFORM("%s: Created %u states", getName().c_str(), nn_->size());
  
      return {solved, approximate};
  }
  
  void ompl::geometric::pRRT::getPlannerData(base::PlannerData &data) const
  {
      Planner::getPlannerData(data);
  
      std::vector<Motion *> motions;
      if (nn_)
          nn_->list(motions);
  
      if (lastGoalMotion_)
          data.addGoalVertex(base::PlannerDataVertex(lastGoalMotion_->state));
  
      for (auto &motion : motions)
      {
          if (motion->parent == nullptr)
              data.addStartVertex(base::PlannerDataVertex(motion->state));
          else
              data.addEdge(base::PlannerDataVertex(motion->parent->state), base::PlannerDataVertex(motion->state));
      }
  }
  
  void ompl::geometric::pRRT::setThreadCount(unsigned int nthreads)
  {
      assert(nthreads > 0);
      threadCount_ = nthreads;
  }
  