ompl::geometric::BiTRRT Class Reference

Bi-directional Transition-based Rapidly-exploring Random Trees. More...

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

Inheritance diagram for ompl::geometric::BiTRRT:

Classes
class	Motion
	Representation of a motion in the search tree. More...

Public Member Functions
	BiTRRT (const base::SpaceInformationPtr &si)
	Constructor.
void	clear () override
	Clear all internal datastructures. Planner settings are not affected. Subsequent calls to solve() will ignore all previous work.
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	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). If clearQuery() is called, the planner may retain prior datastructures generated from a previous query on a new problem definition. The function terminates if the call to ptc returns true.
void	setRange (double distance)
	Set the maximum possible length of any one motion in the search tree. Very short/long motions may inhibit the exploratory capabilities of the planner.
double	getRange () const
	Get the range the planner is using.
void	setTempChangeFactor (double factor)
	Set the factor by which the temperature is increased after a failed transition test. This value should be in the range (0, 1], typically close to zero (default is 0.1). This value is an exponential (e^factor) that is multiplied with the current temperature.
double	getTempChangeFactor () const
	Get the factor by which the temperature is increased after a failed transition.
void	setCostThreshold (double maxCost)
	Set the cost threshold (default is infinity). Any motion cost that is not better than this cost (according to the optimization objective) will not be expanded by the planner.
double	getCostThreshold () const
	Get the cost threshold (default is infinity). Any motion cost that is not better than this cost (according to the optimization objective) will not be expanded by the planner. *‍/.
void	setInitTemperature (double initTemperature)
	Set the initial temperature at the start of planning. Should be high to allow for initial exploration.
double	getInitTemperature () const
	Get the initial temperature at the start of planning.
void	setFrontierThreshold (double frontierThreshold)
	Set the distance between a new state and the nearest neighbor that qualifies a state as being a frontier node.
double	getFrontierThreshold () const
	Get the distance between a new state and the nearest neighbor that qualifies a state as being a frontier node.
void	setFrontierNodeRatio (double frontierNodeRatio)
	Set the ratio between adding non-frontier nodes to frontier nodes. For example: .1 is one non-frontier node for every 10 frontier nodes added.
double	getFrontierNodeRatio () const
	Get the ratio between adding non-frontier nodes to frontier nodes.
template<template< typename T > class NN>
void	setNearestNeighbors ()
	Set a different nearest neighbors datastructure.
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.
ProblemDefinitionPtr &	getProblemDefinition ()
	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() or clearQuery().
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.
virtual void	clearQuery ()
	Clears internal datastructures of any query-specific information from the previous query. Planner settings are not affected. The planner, if able, should retain all datastructures generated from previous queries that can be used to help solve the next query. Note that clear() should also clear all query-specific information along with all other datastructures in the planner. By default clearQuery() calls clear().
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.

Protected Types
enum	GrowResult { FAILED, ADVANCED, SUCCESS }
	The result of a call to extendTree. More...
using	TreeData = std::shared_ptr< NearestNeighbors< Motion * > >
	The nearest-neighbors data structure that contains the entire the tree of motions generated during planning.

Protected Member Functions
void	freeMemory ()
	Free all memory allocated during planning.
Motion *	addMotion (const base::State *state, TreeData &tree, Motion *parent=nullptr)
	Add a state to the given tree. The motion created is returned.
bool	transitionTest (const base::Cost &motionCost)
	Transition test that filters transitions based on the motion cost. If the motion cost is near or below zero, the motion is always accepted, otherwise a probabilistic criterion based on the temperature and motionCost is used.
bool	minExpansionControl (double dist)
	Use frontier node ratio to filter nodes that do not add new information to the search tree.
GrowResult	extendTree (Motion *toMotion, TreeData &tree, Motion *&result)
	Extend tree toward the state in rmotion. Store the result of the extension, if any, in result.
GrowResult	extendTree (Motion *nearest, TreeData &tree, Motion *toMotion, Motion *&result)
	Extend tree from nearest toward toMotion. Store the result of the extension, if any, in result.
bool	connectTrees (Motion *nmotion, TreeData &tree, Motion *xmotion)
	Attempt to connect tree to nmotion, which is in the other tree. xmotion is scratch space and will be overwritten.
double	distanceFunction (const Motion *a, const Motion *b) const
	Compute distance between motions (actually distance between contained states)
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
double	maxDistance_ {0.}
	The maximum length of a motion to be added to a tree.
double	tempChangeFactor_
	The factor by which the temperature is increased after a failed transition test.
base::Cost	bestCost_
	The most desirable (e.g., minimum) cost value in the search tree.
base::Cost	worstCost_
	The least desirable (e.g., maximum) cost value in the search tree.
base::Cost	costThreshold_ {std::numeric_limits<double>::infinity()}
	All motion costs must be better than this cost (default is infinity)
double	initTemperature_ {100.}
	The temperature that planning begins at.
double	frontierThreshold_ {0.}
	The distance between an existing state and a new state that qualifies it as a frontier state.
double	frontierNodeRatio_ {.1}
	The target ratio of non-frontier nodes to frontier nodes.
double	temp_
	The current temperature.
double	nonfrontierCount_
	A count of the number of non-frontier nodes in the trees.
double	frontierCount_
	A count of the number of frontier nodes in the trees.
double	connectionRange_
	The range at which the algorithm will attempt to connect the two trees.
std::pair< Motion *, Motion * >	connectionPoint_ {nullptr, nullptr}
	The most recent connection point for the two trees. Used for PlannerData computation.
TreeData	tStart_
	The start tree.
TreeData	tGoal_
	The goal tree.
ompl::base::OptimizationObjectivePtr	opt_
	The objective (cost function) being optimized.
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.

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

Detailed Description

Bi-directional Transition-based Rapidly-exploring Random Trees.

Short description

This planner grows two T-RRTs, one from the start and one from the goal, and attempts to connect the trees somewhere in the middle. T-RRT is an RRT variant and tree-based motion planner that takes into consideration state costs to compute low-cost paths that follow valleys and saddle points of the configuration-space costmap. It uses transition tests from stochastic optimization methods to accept or reject new potential states.

External documentation

L. Jaillet, J. Cortés, T. Siméon, Sampling-Based Path Planning on Configuration-Space Costmaps, in IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, NO. 4, AUGUST 2010. DOI: 10.1109/TRO.2010.2049527
[PDF]

D. Devaurs, T. Siméon, J. Cortés, Enhancing the Transition-based RRT to Deal with Complex Cost Spaces, in IEEE International Conference on Robotics and Automation (ICRA), 2013, pp. 4120-4125. DOI: 10.1109/ICRA.2013.6631158
[PDF]

Definition at line 133 of file BiTRRT.h.

Member Enumeration Documentation

GrowResult

enum ompl::geometric::BiTRRT::GrowResult

protected

The result of a call to extendTree.

Enumerator
FAILED	No extension was possible.
ADVANCED	Progress was made toward extension.
SUCCESS	The desired state was reached during extension.

Definition at line 328 of file BiTRRT.h.

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

• ompl/geometric/planners/rrt/BiTRRT.h
• ompl/geometric/planners/rrt/src/BiTRRT.cpp