EST.cpp
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34 
35 /* Author: Ryan Luna */
36 
37 #include "ompl/control/planners/est/EST.h"
38 #include "ompl/base/goals/GoalSampleableRegion.h"
39 #include "ompl/tools/config/SelfConfig.h"
40 #include <limits>
41 #include <cassert>
42 
43 ompl::control::EST::EST(const SpaceInformationPtr &si) : base::Planner(si, "EST")
44 {
46  siC_ = si.get();
47 
48  Planner::declareParam<double>("range", this, &EST::setRange, &EST::getRange, "0.:1.:10000.");
49  Planner::declareParam<double>("goal_bias", this, &EST::setGoalBias, &EST::getGoalBias, "0.:.05:1.");
50 }
51 
52 ompl::control::EST::~EST()
53 {
54  freeMemory();
55 }
56 
58 {
59  Planner::setup();
63 
64  tree_.grid.setDimension(projectionEvaluator_->getDimension());
65 }
66 
68 {
69  Planner::clear();
70  sampler_.reset();
71  controlSampler_.reset();
72  freeMemory();
73  tree_.grid.clear();
74  tree_.size = 0;
75  pdf_.clear();
76  lastGoalMotion_ = nullptr;
77 }
78 
80 {
81  for (const auto &it : tree_.grid)
82  {
83  for (const auto &motion : it.second->data.motions_)
84  {
85  if (motion->state)
86  si_->freeState(motion->state);
87  if (motion->control)
88  siC_->freeControl(motion->control);
89  delete motion;
90  }
91  }
92 }
93 
95 {
96  checkValidity();
97  base::Goal *goal = pdef_->getGoal().get();
98  auto *goal_s = dynamic_cast<base::GoalSampleableRegion *>(goal);
99 
100  // Initializing tree with start state(s)
101  while (const base::State *st = pis_.nextStart())
102  {
103  auto *motion = new Motion(siC_);
104  si_->copyState(motion->state, st);
105  siC_->nullControl(motion->control);
106  addMotion(motion);
107  }
108 
109  if (tree_.grid.size() == 0)
110  {
111  OMPL_ERROR("%s: There are no valid initial states!", getName().c_str());
113  }
114 
115  // Ensure that we have a state sampler AND a control sampler
116  if (!sampler_)
117  sampler_ = si_->allocValidStateSampler();
118  if (!controlSampler_)
120 
121  OMPL_INFORM("%s: Starting planning with %u states already in datastructure", getName().c_str(), tree_.size);
122 
123  Motion *solution = nullptr;
124  Motion *approxsol = nullptr;
125  double approxdif = std::numeric_limits<double>::infinity();
126  auto *rmotion = new Motion(siC_);
127  bool solved = false;
128 
129  while (!ptc)
130  {
131  // Select a state to expand the tree from
132  Motion *existing = selectMotion();
133  assert(existing);
134 
135  // sample a random state (with goal biasing) near the state selected for expansion
136  if (goal_s && rng_.uniform01() < goalBias_ && goal_s->canSample())
137  goal_s->sampleGoal(rmotion->state);
138  else
139  {
140  if (!sampler_->sampleNear(rmotion->state, existing->state, maxDistance_))
141  continue;
142  }
143 
144  // Extend a motion toward the state we just sampled
145  unsigned int duration =
146  controlSampler_->sampleTo(rmotion->control, existing->control, existing->state, rmotion->state);
147 
148  // If the system was propagated for a meaningful amount of time, save into the tree
149  if (duration >= siC_->getMinControlDuration())
150  {
151  // create a motion to the resulting state
152  auto *motion = new Motion(siC_);
153  si_->copyState(motion->state, rmotion->state);
154  siC_->copyControl(motion->control, rmotion->control);
155  motion->steps = duration;
156  motion->parent = existing;
157 
158  // save the state
159  addMotion(motion);
160 
161  // Check if this state is the goal state, or improves the best solution so far
162  double dist = 0.0;
163  solved = goal->isSatisfied(motion->state, &dist);
164  if (solved)
165  {
166  approxdif = dist;
167  solution = motion;
168  break;
169  }
170  if (dist < approxdif)
171  {
172  approxdif = dist;
173  approxsol = motion;
174  }
175  }
176  }
177 
178  bool approximate = false;
179  if (solution == nullptr)
180  {
181  solution = approxsol;
182  approximate = true;
183  }
184 
185  // Constructing the solution path
186  if (solution != nullptr)
187  {
188  lastGoalMotion_ = solution;
189 
190  std::vector<Motion *> mpath;
191  while (solution != nullptr)
192  {
193  mpath.push_back(solution);
194  solution = solution->parent;
195  }
196 
197  auto path(std::make_shared<PathControl>(si_));
198  for (int i = mpath.size() - 1; i >= 0; --i)
199  if (mpath[i]->parent)
200  path->append(mpath[i]->state, mpath[i]->control, mpath[i]->steps * siC_->getPropagationStepSize());
201  else
202  path->append(mpath[i]->state);
203  solved = true;
204  pdef_->addSolutionPath(path, approximate, approxdif, getName());
205  }
206 
207  // Cleaning up memory
208  if (rmotion->state)
209  si_->freeState(rmotion->state);
210  if (rmotion->control)
211  siC_->freeControl(rmotion->control);
212  delete rmotion;
213 
214  OMPL_INFORM("%s: Created %u states in %u cells", getName().c_str(), tree_.size, tree_.grid.size());
215 
216  return base::PlannerStatus(solved, approximate);
217 }
218 
220 {
221  GridCell *cell = pdf_.sample(rng_.uniform01());
222  return cell && !cell->data.empty() ? cell->data[rng_.uniformInt(0, cell->data.size() - 1)] : nullptr;
223 }
224 
226 {
228  projectionEvaluator_->computeCoordinates(motion->state, coord);
229  GridCell *cell = tree_.grid.getCell(coord);
230  if (cell)
231  {
232  cell->data.push_back(motion);
233  pdf_.update(cell->data.elem_, 1.0 / cell->data.size());
234  }
235  else
236  {
237  cell = tree_.grid.createCell(coord);
238  cell->data.push_back(motion);
239  tree_.grid.add(cell);
240  cell->data.elem_ = pdf_.add(cell, 1.0);
241  }
242  tree_.size++;
243 }
244 
246 {
247  Planner::getPlannerData(data);
248 
249  std::vector<MotionInfo> motionInfo;
250  tree_.grid.getContent(motionInfo);
251 
252  double stepSize = siC_->getPropagationStepSize();
253 
254  if (lastGoalMotion_)
256 
257  for (auto &mi : motionInfo)
258  for (auto &motion : mi.motions_)
259  {
260  if (motion->parent)
261  {
262  if (data.hasControls())
263  data.addEdge(base::PlannerDataVertex(motion->parent->state), base::PlannerDataVertex(motion->state),
264  PlannerDataEdgeControl(motion->control, motion->steps * stepSize));
265  else
266  data.addEdge(base::PlannerDataVertex(motion->parent->state),
267  base::PlannerDataVertex(motion->state));
268  }
269  else
270  data.addStartVertex(base::PlannerDataVertex(motion->state));
271  }
272 }
double getRange() const
Get the range the planner is using.
Definition: EST.h:114
DirectedControlSamplerPtr allocDirectedControlSampler() const
Allocate an instance of the DirectedControlSampler to use. This will be the default (SimpleDirectedCo...
bool approximateSolutions
Flag indicating whether the planner is able to compute approximate solutions.
Definition: Planner.h:203
Object containing planner generated vertex and edge data. It is assumed that all vertices are unique...
Definition: PlannerData.h:174
double getPropagationStepSize() const
Propagation is performed at integer multiples of a specified step size. This function returns the val...
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: EST.cpp:94
unsigned int getMinControlDuration() const
Get the minimum number of steps a control is propagated for.
void addMotion(Motion *motion)
Add a motion to the exploration tree.
Definition: EST.cpp:225
base::ProjectionEvaluatorPtr projectionEvaluator_
This algorithm uses a discretization (a grid) to guide the exploration. The exploration is imposed on...
Definition: EST.h:244
Control * control
The control contained by the motion.
Definition: EST.h:165
double getGoalBias() const
Get the goal bias the planner is using.
Definition: EST.h:98
void nullControl(Control *control) const
Make the control have no effect if it were to be applied to a state for any amount of time...
DirectedControlSamplerPtr controlSampler_
Directed control sampler.
Definition: EST.h:234
void clear() override
Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() wil...
Definition: EST.cpp:67
Motion * selectMotion()
Select a motion to continue the expansion of the tree from.
Definition: EST.cpp:219
void clear()
Clears the PDF.
Definition: PDF.h:242
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: EST.cpp:245
unsigned int addGoalVertex(const PlannerDataVertex &v)
Adds the given vertex to the graph data, and marks it as a start vertex. The vertex index is returned...
Abstract definition of goals.
Definition: Goal.h:62
CellPDF pdf_
The PDF used for selecting a cell from which to sample a motion.
Definition: EST.h:257
Encapsulate a termination condition for a motion planner. Planners will call operator() to decide whe...
Motion * lastGoalMotion_
The most recent goal motion. Used for PlannerData computation.
Definition: EST.h:260
_T data
The data we store in the cell.
Definition: Grid.h:60
Representation of an edge in PlannerData for planning with controls. This structure encodes a specifi...
Definition: PlannerData.h:60
base::ValidStateSamplerPtr sampler_
Valid state sampler.
Definition: EST.h:231
double goalBias_
The fraction of time the goal is picked as the state to expand towards (if such a state is available)...
Definition: EST.h:248
TreeData tree_
The exploration tree constructed by this algorithm.
Definition: EST.h:240
ProblemDefinitionPtr pdef_
The user set problem definition.
Definition: Planner.h:409
std::vector< int > Coord
Definition of a coordinate within this grid.
Definition: Grid.h:54
double uniform01()
Generate a random real between 0 and 1.
Definition: RandomNumbers.h:68
Base class for a vertex in the PlannerData structure. All derived classes must implement the clone an...
Definition: PlannerData.h:58
Invalid start state or no start state specified.
Definition: PlannerStatus.h:56
Abstract definition of a goal region that can be sampled.
void copyControl(Control *destination, const Control *source) const
Copy a control to another.
#define OMPL_ERROR(fmt,...)
Log a formatted error string.
Definition: Console.h:64
Motion * parent
The parent motion in the exploration tree.
Definition: EST.h:171
unsigned int size
The total number of motions in the grid.
Definition: EST.h:218
A class to store the exit status of Planner::solve()
Definition: PlannerStatus.h:48
virtual bool addEdge(unsigned int v1, unsigned int v2, const PlannerDataEdge &edge=PlannerDataEdge(), Cost weight=Cost(1.0))
Adds a directed edge between the given vertex indexes. An optional edge structure and weight can be s...
unsigned int addStartVertex(const PlannerDataVertex &v)
Adds the given vertex to the graph data, and marks it as a start vertex. The vertex index is returned...
Definition of an abstract state.
Definition: State.h:49
Representation of a motion.
Definition: EST.h:148
virtual void checkValidity()
Check to see if the planner is in a working state (setup has been called, a goal was set...
Definition: Planner.cpp:101
virtual bool isSatisfied(const State *st) const =0
Return true if the state satisfies the goal constraints.
PlannerInputStates pis_
Utility class to extract valid input states.
Definition: Planner.h:412
A shared pointer wrapper for ompl::control::SpaceInformation.
PlannerSpecs specs_
The specifications of the planner (its capabilities)
Definition: Planner.h:418
const State * nextStart()
Return the next valid start state or nullptr if no more valid start states are available.
Definition: Planner.cpp:227
Definition of a cell in this grid.
Definition: Grid.h:57
void update(Element *elem, const double w)
Updates the data in the given Element with a new weight value.
Definition: PDF.h:155
RNG rng_
The random number generator.
Definition: EST.h:254
void configureProjectionEvaluator(base::ProjectionEvaluatorPtr &proj)
If proj is undefined, it is set to the default projection reported by base::StateSpace::getDefaultPro...
Definition: SelfConfig.cpp:231
_T & sample(double r) const
Returns a piece of data from the PDF according to the input sampling value, which must be between 0 a...
Definition: PDF.h:132
void setRange(double distance)
Set the range the planner is supposed to use.
Definition: EST.h:108
Element * add(const _T &d, const double w)
Adds a piece of data with a given weight to the PDF. Returns a corresponding Element, which can be used to subsequently update or remove the data from the PDF.
Definition: PDF.h:97
virtual bool hasControls() const
Indicate whether any information about controls (ompl::control::Control) is stored in this instance...
base::State * state
The state contained by the motion.
Definition: EST.h:162
const std::string & getName() const
Get the name of the planner.
Definition: Planner.cpp:56
void freeMemory()
Free the memory allocated by this planner.
Definition: EST.cpp:79
void setup() override
Perform extra configuration steps, if needed. This call will also issue a call to ompl::base::SpaceIn...
Definition: EST.cpp:57
void setGoalBias(double goalBias)
In the process of randomly selecting states in the state space to attempt to go towards, the algorithm may in fact choose the actual goal state, if it knows it, with some probability. This probability is a real number between 0.0 and 1.0; its value should usually be around 0.05 and should not be too large. It is probably a good idea to use the default value.
Definition: EST.h:92
void configurePlannerRange(double &range)
Compute what a good length for motion segments is.
Definition: SelfConfig.cpp:225
This class contains methods that automatically configure various parameters for motion planning...
Definition: SelfConfig.h:59
void freeControl(Control *control) const
Free the memory of a control.
double maxDistance_
The maximum length of a motion to be added to a tree.
Definition: EST.h:251
SpaceInformationPtr si_
The space information for which planning is done.
Definition: Planner.h:406
int uniformInt(int lower_bound, int upper_bound)
Generate a random integer within given bounds: [lower_bound, upper_bound].
Definition: RandomNumbers.h:81
const SpaceInformation * siC_
The base::SpaceInformation cast as control::SpaceInformation, for convenience.
Definition: EST.h:237
Grid< MotionInfo > grid
A grid where each cell contains an array of motions.
Definition: EST.h:215
EST(const SpaceInformationPtr &si)
Constructor.
Definition: EST.cpp:43
#define OMPL_INFORM(fmt,...)
Log a formatted information string.
Definition: Console.h:68