ompl::geometric::BITstar Class Reference

Batch Informed Trees (BIT*) More...

#include <ompl/geometric/planners/bitstar/BITstar.h>

Inheritance diagram for ompl::geometric::BITstar:

Classes

class  CostHelper
 A helper class to handle the various heuristic functions in one place. More...
 
class  IdGenerator
 An ID generator class for vertex IDs. More...
 
class  ImplicitGraph
 A conceptual representation of samples as an edge-implicit random geometric graph. More...
 
class  SearchQueue
 A queue of edges to be processed that integrates both the expansion of Vertices and the ordering of the resulting edges. More...
 
class  Vertex
 The vertex of the underlying graphs in BIT*. More...
 

Public Types

typedef std::shared_ptr< VertexVertexPtr
 A vertex shared pointer.
 
typedef std::shared_ptr< const VertexVertexConstPtr
 A constant vertex shared pointer.
 
typedef std::weak_ptr< VertexVertexWeakPtr
 A vertex weak pointer.
 
typedef std::vector< VertexPtrVertexPtrVector
 A vector of shared pointers.
 
typedef std::vector< VertexConstPtrVertexConstPtrVector
 A vector of shared const pointers.
 
typedef unsigned int VertexId
 The vertex id type.
 
typedef std::pair< VertexPtr, VertexPtrVertexPtrPair
 A pair of vertices, i.e., an edge.
 
typedef std::pair< VertexConstPtr, VertexConstPtrVertexConstPtrPair
 A pair of const vertices, i.e., an edge.
 
typedef std::vector< VertexPtrPairVertexPtrPairVector
 A vector of pairs of vertices, i.e., a vector of edges.
 
typedef std::vector< VertexConstPtrPairVertexConstPtrPairVector
 A vector of pairs of const vertices, i.e., a vector of edges.
 
typedef std::shared_ptr< NearestNeighbors< VertexPtr > > VertexPtrNNPtr
 The OMPL::NearestNeighbors structure.
 
typedef std::shared_ptr< CostHelperCostHelperPtr
 A cost helper shared pointer.
 
typedef std::shared_ptr< ImplicitGraphImplicitGraphPtr
 An implicit graph shared pointer.
 
typedef std::shared_ptr< SearchQueueSearchQueuePtr
 An search queue shared pointer.
 
typedef std::function< std::string()> NameFunc
 A utility functor for ImplicitGraph and SearchQueue.
 
- 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.
 

Public Member Functions

 BITstar (const base::SpaceInformationPtr &si, const std::string &name="BITstar")
 Construct!
 
 ~BITstar () override=default
 Destruct!
 
void setup () override
 Setup.
 
void clear () override
 Clear.
 
base::PlannerStatus solve (const base::PlannerTerminationCondition &ptc) override
 Solve.
 
void getPlannerData (base::PlannerData &data) const override
 Get results.
 
std::pair< const ompl::base::State *, const ompl::base::State * > getNextEdgeInQueue ()
 Get the next edge to be processed. Causes vertices in the queue to be expanded (if necessary) and therefore effects the run timings of the algorithm, but helpful for some videos and debugging.
 
ompl::base::Cost getNextEdgeValueInQueue ()
 Get the value of the next edge to be processed. Causes vertices in the queue to be expanded (if necessary) and therefore effects the run timings of the algorithm, but helpful for some videos and debugging.
 
void getEdgeQueue (VertexConstPtrPairVector *edgesInQueue)
 Get the whole messy set of edges in the queue. Expensive but helpful for some videos.
 
void getVertexQueue (VertexConstPtrVector *verticesInQueue)
 Get the whole set of vertices to be expanded. Expensive but helpful for some videos.
 
unsigned int numIterations () const
 Get the number of iterations completed.
 
ompl::base::Cost bestCost () const
 Retrieve the best exact-solution cost found.
 
unsigned int numBatches () const
 Retrieve the number of batches processed as the raw data. (numBatches_)
 
void setRewireFactor (double rewireFactor)
 Set the rewiring scale factor, s, such that r_rrg = s r_rrg*.
 
double getRewireFactor () const
 Get the rewiring scale factor.
 
void setSamplesPerBatch (unsigned int n)
 Set the number of samplers per batch.
 
unsigned int getSamplesPerBatch () const
 Get the number of samplers per batch.
 
void setUseKNearest (bool useKNearest)
 Enable a k-nearest search for instead of an r-disc search.
 
bool getUseKNearest () const
 Get whether a k-nearest search is being used.
 
void setStrictQueueOrdering (bool beStrict)
 Enable "strict sorting" of the edge queue. Rewirings can change the position in the queue of an edge. When strict sorting is enabled, the effected edges are resorted immediately, while disabling strict sorting delays this resorting until the end of the batch.
 
bool getStrictQueueOrdering () const
 Get whether strict queue ordering is in use.
 
void setPruning (bool prune)
 Enable pruning of vertices/samples that CANNOT improve the current solution. When a vertex in the graph is pruned, it's descendents are also pruned (if they also cannot improve the solution) or placed back in the set of free samples (if they could improve the solution). This assures that a uniform density is maintained.
 
bool getPruning () const
 Get whether graph and sample pruning is in use.
 
void setPruneThresholdFraction (double fractionalChange)
 Set the fractional change in the solution cost AND problem measure necessary for pruning to occur.
 
double getPruneThresholdFraction () const
 Get the fractional change in the solution cost AND problem measure necessary for pruning to occur.
 
void setDelayRewiringUntilInitialSolution (bool delayRewiring)
 Delay the consideration of rewiring edges until an initial solution is found. When multiple batches are required to find an initial solution, this can improve the time required to do so, by delaying improvements in the cost-to-come to a connected vertex. As the rewiring edges are considered once an initial solution is found, this has no effect on the theoretical asymptotic optimality of the planner. More...
 
bool getDelayRewiringUntilInitialSolution () const
 Get whether BIT* is delaying rewiring until a solution is found.
 
void setJustInTimeSampling (bool useJit)
 Delay the generation of samples until they are necessary. This only works when using an r-disc connection scheme, and is currently only implemented for problems seeking to minimize path length. This helps reduce the complexity of nearest-neighbour look ups, and can be particularly beneficial in unbounded planning problems where selecting an appropriate bounding box is difficult. With JIT sampling enabled, BIT* can solve planning problems whose state space has infinite boundaries. When enumerating outgoing edges from a vertex, BIT* uses JIT sampling to assure that the area within r of the vertex has been sampled during this batch. This is done in a way that maintains uniform sample distribution and has no effect on the theoretical asymptotic optimality of the planner. More...
 
bool getJustInTimeSampling () const
 Get whether we're using just-in-time sampling.
 
void setDropSamplesOnPrune (bool dropSamples)
 Drop all unconnected samples when pruning, regardless of their heuristic value. This provides a method for BIT* to remove samples that have not been connected to the graph and may be beneficial in problems where portions of the free space are unreachable (i.e., disconnected). BIT* calculates the connection radius for each batch from the underlying uniform distribution of states. The resulting larger connection radius may be detrimental in areas where the graph is dense, but maintains the theoretical asymptotic optimality of the planner. More...
 
bool getDropSamplesOnPrune () const
 Get whether unconnected samples are dropped on pruning.
 
void setStopOnSolnImprovement (bool stopOnChange)
 Stop the planner each time a solution improvement is found. Useful for examining the intermediate solutions found by BIT*.
 
bool getStopOnSolnImprovement () const
 Get whether BIT* stops each time a solution is found.
 
void setConsiderApproximateSolutions (bool findApproximate)
 Set BIT* to consider approximate solutions during its initial search.
 
bool getConsiderApproximateSolutions () const
 Get whether BIT* is considering approximate solutions.
 
template<template< typename T > class NN>
void setNearestNeighbors ()
 Set a different nearest neighbours datastructure.
 
- 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.
 

Additional Inherited Members

- 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::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

Batch Informed Trees (BIT*)

BIT* (Batch Informed Trees) is an anytime asymptotically optimal sampling-based planning algorithm. It approaches problems by assuming that a simple solution exists and only goes onto consider complex solutions when that proves incorrect. It accomplishes this by using heuristics to search in order of decreasing potential solution quality.

Both a k-nearest and r-disc version are available, with the k-nearest selected by default. In general, the r-disc variant considers more connections than the k-nearest. For a small number of specific planning problems, this results in it finding solutions slower than k-nearest (hence the default choice). It is recommended that you try both variants, with the r-disc version being recommended if it finds an initial solution in a suitable amount of time (which it probably will). The difference in this number of connections considered is a RGG theory question, and certainly merits further review.

This implementation of BIT* can handle multiple starts, multiple goals, a variety of optimization objectives (e.g., path length), and with just-in-time sampling, infinite problem domains. Note that for some of optimization objectives, the user must specify a suitable heuristic and that when this heuristic is not specified, it will use the conservative/always admissible zero-heuristic.

This implementation also includes some new advancements, including the ability to prioritize exploration until an initial solution is found (Delayed rewiring), the ability to generate samples only when necessary (Just-in-time sampling), and the ability to periodically remove samples that have yet to be connected to the graph (Sample dropping). With just-in-time sampling, BIT* can even solve planning problems with infinite state space boundaries, i.e., (-inf, inf).

Associated publication:

J. D. Gammell, S. S. Srinivasa, T. D. Barfoot, "Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs," In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Seattle, WA, USA, 26-30 May 2015. DOI: 10.1109/ICRA.2015.7139620. Illustration video.

Definition at line 107 of file BITstar.h.

Member Function Documentation

◆ setDelayRewiringUntilInitialSolution()

void ompl::geometric::BITstar::setDelayRewiringUntilInitialSolution ( bool  delayRewiring)

Delay the consideration of rewiring edges until an initial solution is found. When multiple batches are required to find an initial solution, this can improve the time required to do so, by delaying improvements in the cost-to-come to a connected vertex. As the rewiring edges are considered once an initial solution is found, this has no effect on the theoretical asymptotic optimality of the planner.

Definition at line 1124 of file BITstar.cpp.

◆ setDropSamplesOnPrune()

void ompl::geometric::BITstar::setDropSamplesOnPrune ( bool  dropSamples)

Drop all unconnected samples when pruning, regardless of their heuristic value. This provides a method for BIT* to remove samples that have not been connected to the graph and may be beneficial in problems where portions of the free space are unreachable (i.e., disconnected). BIT* calculates the connection radius for each batch from the underlying uniform distribution of states. The resulting larger connection radius may be detrimental in areas where the graph is dense, but maintains the theoretical asymptotic optimality of the planner.

Definition at line 1144 of file BITstar.cpp.

◆ setJustInTimeSampling()

void ompl::geometric::BITstar::setJustInTimeSampling ( bool  useJit)

Delay the generation of samples until they are necessary. This only works when using an r-disc connection scheme, and is currently only implemented for problems seeking to minimize path length. This helps reduce the complexity of nearest-neighbour look ups, and can be particularly beneficial in unbounded planning problems where selecting an appropriate bounding box is difficult. With JIT sampling enabled, BIT* can solve planning problems whose state space has infinite boundaries. When enumerating outgoing edges from a vertex, BIT* uses JIT sampling to assure that the area within r of the vertex has been sampled during this batch. This is done in a way that maintains uniform sample distribution and has no effect on the theoretical asymptotic optimality of the planner.

Definition at line 1134 of file BITstar.cpp.


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