#include <ompl/geometric/planners/sst/SST.h>

Classes | |
class | Motion |
Representation of a motion. More... | |
class | Witness |
Public Member Functions | |
SST (const base::SpaceInformationPtr &si) | |
Constructor. | |
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. | |
base::PlannerStatus | solve (const base::PlannerTerminationCondition &ptc) override |
Continue solving for some amount of time. Return true if solution was found. | |
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). | |
void | clear () override |
Clear datastructures. Call this function if the input data to the planner has changed and you do not want to continue planning. | |
void | setGoalBias (double goalBias) |
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. | |
void | setSelectionRadius (double selectionRadius) |
Set the radius for selecting nodes relative to random sample. More... | |
double | getSelectionRadius () const |
Get the selection radius the planner is using. | |
void | setPruningRadius (double pruningRadius) |
Set the radius for pruning nodes. More... | |
double | getPruningRadius () const |
Get the pruning radius the planner is using. | |
template<template< typename T > class NN> | |
void | setNearestNeighbors () |
Set a different nearest neighbors datastructure. | |
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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. | |
Protected Member Functions | |
Motion * | selectNode (Motion *sample) |
Finds the best node in the tree withing the selection radius around a random sample. | |
Witness * | findClosestWitness (Motion *node) |
Find the closest witness node to a newly generated potential node. | |
base::State * | monteCarloProp (Motion *m) |
Randomly propagate a new edge. | |
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) | |
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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. | |
std::shared_ptr< NearestNeighbors< Motion * > > | witnesses_ |
A nearest-neighbors datastructure containing the tree of witness 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_ {5.} |
The maximum length of a motion to be added to a tree. | |
double | selectionRadius_ {5.} |
The radius for determining the node selected for extension. | |
double | pruningRadius_ {3.} |
The radius for determining the size of the pruning region. | |
RNG | rng_ |
The random number generator. | |
std::vector< base::State * > | prevSolution_ |
The best solution we found so far. | |
base::Cost | prevSolutionCost_ |
The best solution cost we found so far. | |
base::OptimizationObjectivePtr | opt_ |
The optimization objective. | |
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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 | |
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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. | |
Detailed Description
- Short description
- SST (Stable Sparse RRT) is an asymptotically near-optimal incremental sampling-based motion planning algorithm. It is recommended for geometric problems to use an alternative method that makes use of a steering function. Using SST for geometric problems does not take advantage of this function.
- External documentation
- Yanbo Li, Zakary Littlefield, Kostas E. Bekris, Sampling-based Asymptotically Optimal Sampling-based Kinodynamic Planning. [PDF]
Member Function Documentation
◆ setGoalBias()
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inline |
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.
◆ setPruningRadius()
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inline |
Set the radius for pruning nodes.
This is the radius used to surround nodes in the witness set. Within this radius around a state in the witness set, only one active tree node can exist. This limits the size of the tree and forces computation to focus on low path costs nodes. If this value is too large, narrow passages will be impossible to traverse. In addition, children nodes may be removed if they are not at least this distance away from their parent nodes.
◆ setRange()
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inline |
◆ setSelectionRadius()
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inline |
Set the radius for selecting nodes relative to random sample.
This radius is used to mimic behavior of RRT* in that it promotes extending from nodes with good path cost from the root of the tree. Making this radius larger will provide higher quality paths, but has two major drawbacks; exploration will occur much more slowly and exploration around the boundary of the state space may become impossible.
The documentation for this class was generated from the following files: