ompl::geometric::RRTsharp Class Reference

Optimal Rapidly-exploring Random Trees Maintaining An Optimal Tree. More...

`#include <ompl/geometric/planners/rrt/RRTsharp.h>`

Inheritance diagram for ompl::geometric::RRTsharp:

## Public Member Functions | |

RRTsharp (const base::SpaceInformationPtr &si) | |

void | setEpsilon (double epsilon) |

Overwrite of RRTXstatic setEpsilon. It does nothing but warn the user that this parameter cannot be changed. | |

Public Member Functions inherited from ompl::geometric::RRTXstatic | |

RRTXstatic (const base::SpaceInformationPtr &si) | |

virtual void | getPlannerData (base::PlannerData &data) const |

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). | |

virtual base::PlannerStatus | solve (const base::PlannerTerminationCondition &ptc) |

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. | |

virtual void | clear () |

Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work. | |

virtual void | setup () |

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 | setGoalBias (double goalBias) |

Set the goal bias. More... | |

double | getGoalBias () const |

Get the goal bias the planner is using. | |

void | setInformedSampling (bool informedSampling) |

Use direct sampling of the heuristic for the generation of random samples (e.g., x_rand). If a direct sampling method is not defined for the objective, rejection sampling will be used by default. | |

bool | getInformedSampling () const |

Get the state direct heuristic sampling. | |

void | setSampleRejection (bool reject) |

Controls whether heuristic rejection is used on samples (e.g., x_rand) | |

bool | getSampleRejection () const |

Get the state of the sample rejection option. | |

void | setNumSamplingAttempts (unsigned int numAttempts) |

Set the number of attempts to make while performing rejection or informed sampling. | |

unsigned int | getNumSamplingAttempts () const |

Get the number of attempts to make while performing rejection or informed sampling. | |

double | getEpsilon () const |

Get the threshold epsilon 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. | |

void | setRewireFactor (double rewireFactor) |

Set the rewiring scale factor, s, such that r_rrg = s r_rrg* (or k_rrg = s k_rrg*) | |

double | getRewireFactor () const |

Set the rewiring scale factor, s, such that r_rrg = s r_rrg* > r_rrg* (or k_rrg = s k_rrg* > k_rrg*) | |

template<template< typename T > class NN> | |

void | setNearestNeighbors () |

Set a different nearest neighbors datastructure. | |

void | setKNearest (bool useKNearest) |

Use a k-nearest search for rewiring instead of a r-disc search. | |

bool | getKNearest () const |

Get the state of using a k-nearest search for rewiring. | |

void | setUpdateChildren (bool val) |

Set whether or not to always propagate cost updates to children. | |

bool | getUpdateChildren () const |

True if the cost is always propagate to children. | |

void | setVariant (const int variant) |

Set variant used for rejection sampling. | |

int | getVariant () const |

Get variant used for rejection sampling. | |

void | setAlpha (const double a) |

Set the value alpha used for rejection sampling. | |

double | getAlpha () const |

Get the value alpha used for rejection sampling. | |

unsigned int | numIterations () const |

ompl::base::Cost | bestCost () const |

Public Member Functions inherited from ompl::base::Planner | |

Planner (const Planner &)=delete | |

Planner & | operator= (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 SpaceInformationPtr & | getSpaceInformation () const |

Get the space information this planner is using. | |

const ProblemDefinitionPtr & | getProblemDefinition () const |

Get the problem definition the planner is trying to solve. | |

const PlannerInputStates & | getPlannerInputStates () 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 PlannerSpecs & | getSpecs () 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. | |

ParamSet & | params () |

Get the parameters for this planner. | |

const ParamSet & | params () const |

Get the parameters for this planner. | |

const PlannerProgressProperties & | getPlannerProgressProperties () 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. | |

## 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, PlannerProgressProperty > | PlannerProgressProperties |

A dictionary which maps the name of a progress property to the function to be used for querying that property. | |

Protected Member Functions inherited from ompl::geometric::RRTXstatic | |

void | allocSampler () |

Create the samplers. | |

bool | sampleUniform (base::State *statePtr) |

Generate a sample. | |

void | freeMemory () |

Free the memory allocated by this planner. | |

double | distanceFunction (const Motion *a, const Motion *b) const |

Compute distance between motions (actually distance between contained states) | |

void | updateQueue (Motion *x) |

Update (or add) a motion in the queue. | |

void | removeFromParent (Motion *m) |

Removes the given motion from the parent's child list. | |

void | getNeighbors (Motion *motion) const |

Gets the neighbours of a given motion, using either k-nearest of radius as appropriate. | |

void | calculateRewiringLowerBounds () |

Calculate the k_RRG* and r_RRG* terms. | |

void | calculateRRG () |

Calculate the rrg_r_ and rrg_k_ terms. | |

bool | includeVertex (const Motion *x) const |

Test if the vertex should be included according to the variant in use. | |

std::string | numIterationsProperty () const |

std::string | bestCostProperty () const |

std::string | numMotionsProperty () const |

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 inherited from ompl::geometric::RRTXstatic | |

base::StateSamplerPtr | sampler_ |

State sampler. | |

base::InformedSamplerPtr | infSampler_ |

An informed sampler. | |

std::shared_ptr< NearestNeighbors< Motion * > > | nn_ |

A nearest-neighbors datastructure containing the tree of motions. | |

double | goalBias_ {.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. | |

bool | useKNearest_ {true} |

Option to use k-nearest search for rewiring. | |

double | rewireFactor_ {1.1} |

The rewiring factor, s, so that r_rrg = s r_rrg* > r_rrg* (or k_rrg = s k_rrg* > k_rrg*) | |

double | k_rrt_ {0u} |

A constant for k-nearest rewiring calculations. | |

double | r_rrt_ {0.} |

A constant for r-disc rewiring calculations. | |

base::OptimizationObjectivePtr | opt_ |

Objective we're optimizing. | |

Motion * | lastGoalMotion_ {nullptr} |

The most recent goal motion. Used for PlannerData computation. | |

std::vector< Motion * > | goalMotions_ |

A list of states in the tree that satisfy the goal condition. | |

base::Cost | bestCost_ {std::numeric_limits<double>::quiet_NaN()} |

Best cost found so far by algorithm. | |

unsigned int | iterations_ {0u} |

Number of iterations the algorithm performed. | |

MotionCompare | mc_ |

Comparator of motions, used to order the queue. | |

BinaryHeap< Motion *, MotionCompare > | q_ |

Queue to order the nodes to update. | |

base::Cost | epsilonCost_ {0.} |

Threshold for the propagation of information. | |

bool | updateChildren_ {true} |

Whether or not to propagate the cost to children if the update is less than epsilon. | |

double | rrg_r_ |

Current value of the radius used for the neighbors. | |

unsigned int | rrg_k_ |

Current value of the number of neighbors used. | |

int | variant_ {0} |

Variant used for rejection sampling. | |

double | alpha_ {1.} |

Alpha parameter, scaling the rejection sampling tests. | |

bool | useInformedSampling_ {false} |

Option to use informed sampling. | |

bool | useRejectionSampling_ {false} |

The status of the sample rejection parameter. | |

unsigned int | numSampleAttempts_ {100u} |

The number of attempts to make at informed sampling. | |

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. | |

## Detailed Description

Optimal Rapidly-exploring Random Trees Maintaining An Optimal Tree.

- Short description
- RRT# is an asymptotically-optimal incremental sampling-based motion planning algorithm. It is similar from RRTXstatic but maintains an optimal tree, same as RRTXstatic with a treshold 0.

The parameters are the same as RRTXstatic except for the parameter epsilon.

- External documentation
- M. Otte & E. Frazzoli - RRTX : Real-Time Motion Planning/Replanning for Environments with Unpredictable Obstacles, Algorithmic Foundations of Robotics XI, Volume 107 of the series Springer Tracts in Advanced Robotics pp 461-478
- O. Arslan, P. Tsiotras - The role of vertex consistency in sampling-based algorithms for optimal motion planning, http://arxiv.org/pdf/1204.6453
- O. Arslan, P. Tsiotras - Dynamic programming guided exploration for sampling-based motion planning algorithms, 2015 IEEE International Conference on Robotics and Automation (ICRA), pp 4819-4826

Definition at line 67 of file RRTsharp.h.

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

- ompl/geometric/planners/rrt/RRTsharp.h
- ompl/geometric/planners/rrt/src/RRTsharp.cpp