LazyLBTRRT.h
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34 
35 /* Author: Oren Salzman, Mark Moll */
36 
37 #ifndef OMPL_CONTRIB_LAZY_LBTRRT_
38 #define OMPL_CONTRIB_LAZY_LBTRRT_
39 
40 #include "ompl/geometric/planners/PlannerIncludes.h"
41 #include "ompl/datastructures/NearestNeighbors.h"
42 #include "ompl/base/goals/GoalSampleableRegion.h"
43 #include "ompl/datastructures/LPAstarOnGraph.h"
44 
45 #include <fstream>
46 #include <vector>
47 #include <tuple>
48 #include <cassert>
49 
50 #include <boost/graph/graph_traits.hpp>
51 #include <boost/graph/adjacency_list.hpp>
52 
53 namespace ompl
54 {
55  namespace geometric
56  {
58  class LazyLBTRRT : public base::Planner
59  {
60  public:
62  LazyLBTRRT(const base::SpaceInformationPtr &si);
63 
64  ~LazyLBTRRT() override;
65 
66  void getPlannerData(base::PlannerData &data) const override;
67 
68  base::PlannerStatus solve(const base::PlannerTerminationCondition &ptc) override;
69 
70  void clear() override;
71 
81  void setGoalBias(double goalBias)
82  {
83  goalBias_ = goalBias;
84  }
85 
87  double getGoalBias() const
88  {
89  return goalBias_;
90  }
91 
97  void setRange(double distance)
98  {
99  maxDistance_ = distance;
100  }
101 
103  double getRange() const
104  {
105  return maxDistance_;
106  }
107 
109  template <template <typename T> class NN>
110  void setNearestNeighbors()
111  {
112  if (nn_ && nn_->size() != 0)
113  OMPL_WARN("Calling setNearestNeighbors will clear all states.");
114  clear();
115  nn_ = std::make_shared<NN<Motion *>>();
116  setup();
117  }
118 
119  void setup() override;
120 
122  void setApproximationFactor(double epsilon)
123  {
124  epsilon_ = epsilon;
125  }
126 
128  // Planner progress property functions
129  std::string getIterationCount() const
130  {
131  return std::to_string(iterations_);
132  }
133  std::string getBestCost() const
134  {
135  return std::to_string(bestCost_);
136  }
137 
138  protected:
140  class Motion
141  {
142  public:
143  Motion() = default;
144 
146  Motion(const base::SpaceInformationPtr &si) : state_(si->allocState())
147  {
148  }
149 
150  ~Motion() = default;
151 
153  std::size_t id_;
154 
156  base::State *state_{nullptr};
157  };
158 
159  using WeightProperty = boost::property<boost::edge_weight_t, double>;
160  using BoostGraph = boost::adjacency_list<boost::vecS, // container type for the out edge list
161  boost::vecS, // container type for the vertex list
162  boost::undirectedS, // directedS / undirectedS / bidirectionalS.
163  std::size_t, // vertex properties
164  WeightProperty // edge properties
165  >;
166 
167  friend class CostEstimatorApx; // allow CostEstimatorApx access to private members
168  class CostEstimatorApx
169  {
170  public:
171  CostEstimatorApx(LazyLBTRRT *alg) : alg_(alg)
172  {
173  }
174  double operator()(std::size_t i)
175  {
176  double lb_estimate = (*(alg_->LPAstarLb_))(i);
177  if (lb_estimate != std::numeric_limits<double>::infinity())
178  return lb_estimate;
179 
180  return alg_->distanceFunction(alg_->idToMotionMap_[i], alg_->startMotion_);
181  }
182 
183  private:
184  LazyLBTRRT *alg_;
185  }; // CostEstimatorApx
186 
187  class CostEstimatorLb
188  {
189  public:
190  CostEstimatorLb(base::Goal *goal, std::vector<Motion *> &idToMotionMap)
191  : goal_(goal), idToMotionMap_(idToMotionMap)
192  {
193  }
194  double operator()(std::size_t i)
195  {
196  double dist = 0.0;
197  goal_->isSatisfied(idToMotionMap_[i]->state_, &dist);
198 
199  return dist;
200  }
201 
202  private:
203  base::Goal *goal_;
204  std::vector<Motion *> &idToMotionMap_;
205  }; // CostEstimatorLb
206 
209 
211  void sampleBiased(const base::GoalSampleableRegion *goal_s, base::State *rstate);
212 
214  void freeMemory();
215 
217  double distanceFunction(const base::State *a, const base::State *b) const
218  {
219  return si_->distance(a, b);
220  }
221  double distanceFunction(const Motion *a, const Motion *b) const
222  {
223  return si_->distance(a->state_, b->state_);
224  }
225  bool checkMotion(const base::State *a, const base::State *b) const
226  {
227  return si_->checkMotion(a, b);
228  }
229  bool checkMotion(const Motion *a, const Motion *b) const
230  {
231  return si_->checkMotion(a->state_, b->state_);
232  }
233 
234  Motion *getMotion(std::size_t id) const
235  {
236  assert(idToMotionMap_.size() > id);
237  return idToMotionMap_[id];
238  }
239  void addVertex(const Motion *a)
240  {
241  boost::add_vertex(a->id_, graphApx_);
242  boost::add_vertex(a->id_, graphLb_);
243  }
244 
245  void addEdgeApx(Motion *a, Motion *b, double c)
246  {
247  WeightProperty w(c);
248  boost::add_edge(a->id_, b->id_, w, graphApx_);
249  LPAstarApx_->insertEdge(a->id_, b->id_, c);
250  LPAstarApx_->insertEdge(b->id_, a->id_, c);
251  }
252  void addEdgeLb(const Motion *a, const Motion *b, double c)
253  {
254  WeightProperty w(c);
255  boost::add_edge(a->id_, b->id_, w, graphLb_);
256  LPAstarLb_->insertEdge(a->id_, b->id_, c);
257  LPAstarLb_->insertEdge(b->id_, a->id_, c);
258  }
259  bool edgeExistsApx(std::size_t a, std::size_t b)
260  {
261  return boost::edge(a, b, graphApx_).second;
262  }
263  bool edgeExistsApx(const Motion *a, const Motion *b)
264  {
265  return edgeExistsApx(a->id_, b->id_);
266  }
267  bool edgeExistsLb(const Motion *a, const Motion *b)
268  {
269  return boost::edge(a->id_, b->id_, graphLb_).second;
270  }
271  void removeEdgeLb(const Motion *a, const Motion *b)
272  {
273  boost::remove_edge(a->id_, b->id_, graphLb_);
274  LPAstarLb_->removeEdge(a->id_, b->id_);
275  LPAstarLb_->removeEdge(b->id_, a->id_);
276  }
277  std::tuple<Motion *, base::State *, double> rrtExtend(const base::GoalSampleableRegion *goal_s,
278  base::State *xstate, Motion *rmotion,
279  double &approxdif);
281  base::State *xstate, Motion *rmotion, double &approxdif);
282  Motion *createMotion(const base::GoalSampleableRegion *goal_s, const base::State *st);
283  Motion *createGoalMotion(const base::GoalSampleableRegion *goal_s);
284 
285  void closeBounds(const base::PlannerTerminationCondition &ptc);
286 
288  double getApproximationFactor() const
289  {
290  return epsilon_;
291  }
292 
294  base::StateSamplerPtr sampler_;
295 
297  std::shared_ptr<NearestNeighbors<Motion *>> nn_;
298 
301  double goalBias_{0.05};
302 
304  double maxDistance_{0.};
305 
307  RNG rng_;
308 
310  double epsilon_{.4};
311 
314 
315  BoostGraph graphLb_;
316  BoostGraph graphApx_;
317  Motion *startMotion_;
318  Motion *goalMotion_{nullptr}; // root of LPAstarApx_
319  LPAstarApx *LPAstarApx_{nullptr}; // rooted at target
320  LPAstarLb *LPAstarLb_{nullptr}; // rooted at source
321  std::vector<Motion *> idToMotionMap_;
322 
324  // Planner progress properties
326  unsigned int iterations_{0};
328  double bestCost_;
329  };
330  }
331 }
332 
333 #endif // OMPL_CONTRIB_LAZY_LBTRRT_
Random number generation. An instance of this class cannot be used by multiple threads at once (membe...
Definition: RandomNumbers.h:89
std::size_t id_
The id of the motion.
Definition: LazyLBTRRT.h:249
double goalBias_
The fraction of time the goal is picked as the state to expand towards (if such a state is available)
Definition: LazyLBTRRT.h:397
void getPlannerData(base::PlannerData &data) const override
Get information about the current run of the motion planner. Repeated calls to this function will upd...
Definition: LazyLBTRRT.cpp:318
void setApproximationFactor(double epsilon)
Set the apprimation factor.
Definition: LazyLBTRRT.h:218
Definition of an abstract state.
Definition: State.h:113
void setGoalBias(double goalBias)
Set the goal bias.
Definition: LazyLBTRRT.h:177
Rapidly-exploring Random Trees.
Definition: LazyLBTRRT.h:122
double getApproximationFactor() const
Get the apprimation factor.
Definition: LazyLBTRRT.h:384
void setRange(double distance)
Set the range the planner is supposed to use.
Definition: LazyLBTRRT.h:193
double getRange() const
Get the range the planner is using.
Definition: LazyLBTRRT.h:199
Encapsulate a termination condition for a motion planner. Planners will call operator() to decide whe...
base::PlannerStatus solve(const base::PlannerTerminationCondition &ptc) override
Function that can solve the motion planning problem. This function can be called multiple times on th...
Definition: LazyLBTRRT.cpp:122
double maxDistance_
The maximum length of a motion to be added to a tree.
Definition: LazyLBTRRT.h:400
double epsilon_
approximation factor
Definition: LazyLBTRRT.h:406
void sampleBiased(const base::GoalSampleableRegion *goal_s, base::State *rstate)
sample with goal biasing
Definition: LazyLBTRRT.cpp:344
virtual bool isSatisfied(const State *st) const =0
Return true if the state satisfies the goal constraints.
unsigned int iterations_
Number of iterations the algorithm performed.
Definition: LazyLBTRRT.h:422
Abstract definition of goals.
Definition: Goal.h:126
#define OMPL_WARN(fmt,...)
Log a formatted warning string.
Definition: Console.h:66
double distanceFunction(const base::State *a, const base::State *b) const
Compute distance between motions (actually distance between contained states)
Definition: LazyLBTRRT.h:313
RNG rng_
The random number generator.
Definition: LazyLBTRRT.h:403
base::StateSamplerPtr sampler_
State sampler.
Definition: LazyLBTRRT.h:390
Representation of a motion.
Definition: LazyLBTRRT.h:236
double getGoalBias() const
Get the goal bias the planner is using.
Definition: LazyLBTRRT.h:183
Motion * lastGoalMotion_
The most recent goal motion. Used for PlannerData computation.
Definition: LazyLBTRRT.h:409
SpaceInformationPtr si_
The space information for which planning is done.
Definition: Planner.h:474
void freeMemory()
Free the memory allocated by this planner.
Definition: LazyLBTRRT.cpp:106
double bestCost_
Best cost found so far by algorithm.
Definition: LazyLBTRRT.h:424
LazyLBTRRT(const base::SpaceInformationPtr &si)
Constructor.
Definition: LazyLBTRRT.cpp:51
base::State * state_
The state contained by the motion.
Definition: LazyLBTRRT.h:252
Abstract definition of a goal region that can be sampled.
void setNearestNeighbors()
Set a different nearest neighbors datastructure.
Definition: LazyLBTRRT.h:206
std::shared_ptr< NearestNeighbors< Motion * > > nn_
A nearest-neighbors datastructure containing the tree of motions.
Definition: LazyLBTRRT.h:393
void setup() override
Perform extra configuration steps, if needed. This call will also issue a call to ompl::base::SpaceIn...
Definition: LazyLBTRRT.cpp:92
Main namespace. Contains everything in this library.
void clear() override
Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() wil...
Definition: LazyLBTRRT.cpp:77