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RRT.cpp
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00034 
00035 /* Author: Ioan Sucan */
00036 
00037 #include "ompl/geometric/planners/rrt/RRT.h"
00038 #include "ompl/base/GoalSampleableRegion.h"
00039 #include "ompl/datastructures/NearestNeighborsSqrtApprox.h"
00040 #include <limits>
00041 
00042 void ompl::geometric::RRT::clear(void)
00043 {
00044     Planner::clear();
00045     sampler_.reset();
00046     freeMemory();
00047     if (nn_)
00048         nn_->clear();
00049 }
00050 
00051 void ompl::geometric::RRT::setup(void)
00052 {
00053     Planner::setup();
00054     checkMotionLength(this, maxDistance_);
00055 
00056     if (!nn_)
00057         nn_.reset(new NearestNeighborsSqrtApprox<Motion*>());
00058     nn_->setDistanceFunction(boost::bind(&RRT::distanceFunction, this, _1, _2));
00059 }
00060 
00061 void ompl::geometric::RRT::freeMemory(void)
00062 {
00063     if (nn_)
00064     {
00065         std::vector<Motion*> motions;
00066         nn_->list(motions);
00067         for (unsigned int i = 0 ; i < motions.size() ; ++i)
00068         {
00069             if (motions[i]->state)
00070                 si_->freeState(motions[i]->state);
00071             delete motions[i];
00072         }
00073     }
00074 }
00075 
00076 bool ompl::geometric::RRT::solve(const base::PlannerTerminationCondition &ptc)
00077 {
00078     checkValidity();
00079     base::Goal                 *goal   = pdef_->getGoal().get();
00080     base::GoalSampleableRegion *goal_s = dynamic_cast<base::GoalSampleableRegion*>(goal);
00081 
00082     if (!goal)
00083     {
00084         msg_.error("Goal undefined");
00085         return false;
00086     }
00087 
00088     while (const base::State *st = pis_.nextStart())
00089     {
00090         Motion *motion = new Motion(si_);
00091         si_->copyState(motion->state, st);
00092         nn_->add(motion);
00093     }
00094 
00095     if (nn_->size() == 0)
00096     {
00097         msg_.error("There are no valid initial states!");
00098         return false;
00099     }
00100 
00101     if (!sampler_)
00102         sampler_ = si_->allocManifoldStateSampler();
00103 
00104     msg_.inform("Starting with %u states", nn_->size());
00105 
00106     Motion *solution  = NULL;
00107     Motion *approxsol = NULL;
00108     double  approxdif = std::numeric_limits<double>::infinity();
00109     Motion *rmotion   = new Motion(si_);
00110     base::State *rstate = rmotion->state;
00111     base::State *xstate = si_->allocState();
00112 
00113     while (ptc() == false)
00114     {
00115 
00116         /* sample random state (with goal biasing) */
00117         if (goal_s && rng_.uniform01() < goalBias_ && goal_s->canSample())
00118             goal_s->sampleGoal(rstate);
00119         else
00120             sampler_->sampleUniform(rstate);
00121 
00122         /* find closest state in the tree */
00123         Motion *nmotion = nn_->nearest(rmotion);
00124         base::State *dstate = rstate;
00125 
00126         /* find state to add */
00127         double d = si_->distance(nmotion->state, rstate);
00128         if (d > maxDistance_)
00129         {
00130             si_->getStateManifold()->interpolate(nmotion->state, rstate, maxDistance_ / d, xstate);
00131             dstate = xstate;
00132         }
00133 
00134         if (si_->checkMotion(nmotion->state, dstate))
00135         {
00136             /* create a motion */
00137             Motion *motion = new Motion(si_);
00138             si_->copyState(motion->state, dstate);
00139             motion->parent = nmotion;
00140 
00141             nn_->add(motion);
00142             double dist = 0.0;
00143             bool solved = goal->isSatisfied(motion->state, &dist);
00144             if (solved)
00145             {
00146                 approxdif = dist;
00147                 solution = motion;
00148                 break;
00149             }
00150             if (dist < approxdif)
00151             {
00152                 approxdif = dist;
00153                 approxsol = motion;
00154             }
00155         }
00156     }
00157 
00158     bool approximate = false;
00159     if (solution == NULL)
00160     {
00161         solution = approxsol;
00162         approximate = true;
00163     }
00164 
00165     if (solution != NULL)
00166     {
00167         /* construct the solution path */
00168         std::vector<Motion*> mpath;
00169         while (solution != NULL)
00170         {
00171             mpath.push_back(solution);
00172             solution = solution->parent;
00173         }
00174 
00175         /* set the solution path */
00176         PathGeometric *path = new PathGeometric(si_);
00177            for (int i = mpath.size() - 1 ; i >= 0 ; --i)
00178             path->states.push_back(si_->cloneState(mpath[i]->state));
00179         goal->setDifference(approxdif);
00180         goal->setSolutionPath(base::PathPtr(path), approximate);
00181 
00182         if (approximate)
00183             msg_.warn("Found approximate solution");
00184     }
00185 
00186     si_->freeState(xstate);
00187     if (rmotion->state)
00188         si_->freeState(rmotion->state);
00189     delete rmotion;
00190 
00191     msg_.inform("Created %u states", nn_->size());
00192 
00193     return goal->isAchieved();
00194 }
00195 
00196 void ompl::geometric::RRT::getPlannerData(base::PlannerData &data) const
00197 {
00198     Planner::getPlannerData(data);
00199 
00200     std::vector<Motion*> motions;
00201     if (nn_)
00202         nn_->list(motions);
00203 
00204     for (unsigned int i = 0 ; i < motions.size() ; ++i)
00205         data.recordEdge(motions[i]->parent ? motions[i]->parent->state : NULL, motions[i]->state);
00206 }
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