ompl::geometric::LazyLBTRRT Class Reference

Rapidly-exploring Random Trees. More...

#include <ompl/geometric/planners/rrt/LazyLBTRRT.h>

Inheritance diagram for ompl::geometric::LazyLBTRRT:

Classes

class  CostEstimatorApx
 
class  CostEstimatorLb
 
class  Motion
 Representation of a motion. More...
 

Public Member Functions

 LazyLBTRRT (const base::SpaceInformationPtr &si)
 Constructor.
 
void getPlannerData (base::PlannerData &data) const override
 Get information about the current run of the motion planner. Repeated calls to this function will update data (only additions are made). This is useful to see what changed in the exploration datastructure, between calls to solve(), for example (without calling clear() in between).
 
base::PlannerStatus solve (const base::PlannerTerminationCondition &ptc) override
 Function that can solve the motion planning problem. This function can be called multiple times on the same problem, without calling clear() in between. This allows the planner to continue work for more time on an unsolved problem, for example. If this option is used, it is assumed the problem definition is not changed (unpredictable results otherwise). The only change in the problem definition that is accounted for is the addition of starting or goal states (but not changing previously added start/goal states). The function terminates if the call to ptc returns true.
 
void clear () override
 Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.
 
void setGoalBias (double goalBias)
 Set the goal bias. More...
 
double getGoalBias () const
 Get the goal bias the planner is using.
 
void setRange (double distance)
 Set the range the planner is supposed to use. More...
 
double getRange () const
 Get the range the planner is using.
 
template<template< typename T > class NN>
void setNearestNeighbors ()
 Set a different nearest neighbors datastructure.
 
void setup () override
 Perform extra configuration steps, if needed. This call will also issue a call to ompl::base::SpaceInformation::setup() if needed. This must be called before solving.
 
void setApproximationFactor (double epsilon)
 Set the apprimation factor.
 
std::string getIterationCount () const
 
std::string getBestCost () const
 
- Public Member Functions inherited from ompl::base::Planner
 Planner (const Planner &)=delete
 
Planneroperator= (const Planner &)=delete
 
 Planner (SpaceInformationPtr si, std::string name)
 Constructor.
 
virtual ~Planner ()=default
 Destructor.
 
template<class T >
T * as ()
 Cast this instance to a desired type. More...
 
template<class T >
const T * as () const
 Cast this instance to a desired type. More...
 
const SpaceInformationPtrgetSpaceInformation () const
 Get the space information this planner is using.
 
const ProblemDefinitionPtrgetProblemDefinition () const
 Get the problem definition the planner is trying to solve.
 
const PlannerInputStatesgetPlannerInputStates () const
 Get the planner input states.
 
virtual void setProblemDefinition (const ProblemDefinitionPtr &pdef)
 Set the problem definition for the planner. The problem needs to be set before calling solve(). Note: If this problem definition replaces a previous one, it may also be necessary to call clear().
 
PlannerStatus solve (const PlannerTerminationConditionFn &ptc, double checkInterval)
 Same as above except the termination condition is only evaluated at a specified interval.
 
PlannerStatus solve (double solveTime)
 Same as above except the termination condition is solely a time limit: the number of seconds the algorithm is allowed to spend planning.
 
const std::string & getName () const
 Get the name of the planner.
 
void setName (const std::string &name)
 Set the name of the planner.
 
const PlannerSpecsgetSpecs () const
 Return the specifications (capabilities of this planner)
 
virtual void checkValidity ()
 Check to see if the planner is in a working state (setup has been called, a goal was set, the input states seem to be in order). In case of error, this function throws an exception.
 
bool isSetup () const
 Check if setup() was called for this planner.
 
ParamSetparams ()
 Get the parameters for this planner.
 
const ParamSetparams () const
 Get the parameters for this planner.
 
const PlannerProgressPropertiesgetPlannerProgressProperties () const
 Retrieve a planner's planner progress property map.
 
virtual void printProperties (std::ostream &out) const
 Print properties of the motion planner.
 
virtual void printSettings (std::ostream &out) const
 Print information about the motion planner's settings.
 

Protected Types

typedef boost::property< boost::edge_weight_t, double > WeightProperty
 
typedef boost::adjacency_list< boost::vecS, boost::vecS, boost::undirectedS, std::size_t, WeightProperty > BoostGraph
 
typedef LPAstarOnGraph< BoostGraph, CostEstimatorApxLPAstarApx
 
typedef LPAstarOnGraph< BoostGraph, CostEstimatorLbLPAstarLb
 

Protected Member Functions

void sampleBiased (const base::GoalSampleableRegion *goal_s, base::State *rstate)
 sample with goal biasing
 
void freeMemory ()
 Free the memory allocated by this planner.
 
double distanceFunction (const base::State *a, const base::State *b) const
 Compute distance between motions (actually distance between contained states)
 
double distanceFunction (const Motion *a, const Motion *b) const
 
bool checkMotion (const base::State *a, const base::State *b) const
 
bool checkMotion (const Motion *a, const Motion *b) const
 
MotiongetMotion (std::size_t id) const
 
void addVertex (const Motion *a)
 
void addEdgeApx (Motion *a, Motion *b, double c)
 
void addEdgeLb (const Motion *a, const Motion *b, double c)
 
bool edgeExistsApx (std::size_t a, std::size_t b)
 
bool edgeExistsApx (const Motion *a, const Motion *b)
 
bool edgeExistsLb (const Motion *a, const Motion *b)
 
void removeEdgeLb (const Motion *a, const Motion *b)
 
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)
 
MotioncreateMotion (const base::GoalSampleableRegion *goal_s, const base::State *st)
 
MotioncreateGoalMotion (const base::GoalSampleableRegion *goal_s)
 
void closeBounds (const base::PlannerTerminationCondition &ptc)
 
double getApproximationFactor () const
 Get the apprimation factor.
 
- Protected Member Functions inherited from ompl::base::Planner
template<typename T , typename PlannerType , typename SetterType , typename GetterType >
void declareParam (const std::string &name, const PlannerType &planner, const SetterType &setter, const GetterType &getter, const std::string &rangeSuggestion="")
 This function declares a parameter for this planner instance, and specifies the setter and getter functions.
 
template<typename T , typename PlannerType , typename SetterType >
void declareParam (const std::string &name, const PlannerType &planner, const SetterType &setter, const std::string &rangeSuggestion="")
 This function declares a parameter for this planner instance, and specifies the setter function.
 
void addPlannerProgressProperty (const std::string &progressPropertyName, const PlannerProgressProperty &prop)
 Add a planner progress property called progressPropertyName with a property querying function prop to this planner's progress property map.
 

Protected Attributes

base::StateSamplerPtr sampler_
 State sampler.
 
std::shared_ptr< NearestNeighbors< Motion * > > nn_
 A nearest-neighbors datastructure containing the tree of motions.
 
double goalBias_ {0.05}
 The fraction of time the goal is picked as the state to expand towards (if such a state is available)
 
double maxDistance_ {0.}
 The maximum length of a motion to be added to a tree.
 
RNG rng_
 The random number generator.
 
double epsilon_ {.4}
 approximation factor
 
MotionlastGoalMotion_ {nullptr}
 The most recent goal motion. Used for PlannerData computation.
 
BoostGraph graphLb_
 
BoostGraph graphApx_
 
MotionstartMotion_
 
MotiongoalMotion_ {nullptr}
 
LPAstarApxLPAstarApx_ {nullptr}
 
LPAstarLbLPAstarLb_ {nullptr}
 
std::vector< Motion * > idToMotionMap_
 
unsigned int iterations_ {0}
 Number of iterations the algorithm performed.
 
double bestCost_
 Best cost found so far by algorithm.
 
- Protected Attributes inherited from ompl::base::Planner
SpaceInformationPtr si_
 The space information for which planning is done.
 
ProblemDefinitionPtr pdef_
 The user set problem definition.
 
PlannerInputStates pis_
 Utility class to extract valid input states.
 
std::string name_
 The name of this planner.
 
PlannerSpecs specs_
 The specifications of the planner (its capabilities)
 
ParamSet params_
 A map from parameter names to parameter instances for this planner. This field is populated by the declareParam() function.
 
PlannerProgressProperties plannerProgressProperties_
 A mapping between this planner's progress property names and the functions used for querying those progress properties.
 
bool setup_
 Flag indicating whether setup() has been called.
 

Friends

class CostEstimatorApx
 

Additional Inherited Members

- Public Types inherited from ompl::base::Planner
typedef std::function< std::string()> PlannerProgressProperty
 Definition of a function which returns a property about the planner's progress that can be queried by a benchmarking routine.
 
typedef std::map< std::string, PlannerProgressPropertyPlannerProgressProperties
 A dictionary which maps the name of a progress property to the function to be used for querying that property.
 

Detailed Description

Rapidly-exploring Random Trees.

Definition at line 58 of file LazyLBTRRT.h.

Member Function Documentation

◆ setGoalBias()

void ompl::geometric::LazyLBTRRT::setGoalBias ( double  goalBias)
inline

Set the goal bias.

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 at line 81 of file LazyLBTRRT.h.

◆ setRange()

void ompl::geometric::LazyLBTRRT::setRange ( double  distance)
inline

Set the range the planner is supposed to use.

This parameter greatly influences the runtime of the algorithm. It represents the maximum length of a motion to be added in the tree of motions.

Definition at line 97 of file LazyLBTRRT.h.


The documentation for this class was generated from the following files: