ompl::control::PDST Class Reference

Path-Directed Subdivision Tree. More...

#include <ompl/control/planners/pdst/PDST.h>

Inheritance diagram for ompl::control::PDST:

Classes

struct  Cell
 Cell is a Binary Space Partition. More...
 
struct  Motion
 Class representing the tree of motions exploring the state space. More...
 
struct  MotionCompare
 Comparator used to order motions in the priority queue. More...
 

Public Member Functions

 PDST (const SpaceInformationPtr &si)
 
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 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
 Extracts the planner data from the priority queue into data.
 
void setProjectionEvaluator (const base::ProjectionEvaluatorPtr &projectionEvaluator)
 Set the projection evaluator. This class is able to compute the projection of a given state.
 
void setProjectionEvaluator (const std::string &name)
 Set the projection evaluator (select one from the ones registered with the state space).
 
const base::ProjectionEvaluatorPtrgetProjectionEvaluator () const
 Get the projection evaluator.
 
*void setGoalBias (double goalBias)
 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.
 
double getGoalBias () const
 Get the goal bias the planner is using */.
 
- 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 Member Functions

void addMotion (Motion *motion, Cell *cell, base::State *, base::State *, base::EuclideanProjection &, base::EuclideanProjection &)
 Inserts the motion into the appropriate cells, splitting the motion as necessary. motion is assumed to be fully contained within cell.
 
void updateHeapElement (Motion *motion)
 Either update heap after motion's priority has changed or insert motion into heap.
 
MotionpropagateFrom (Motion *motion, base::State *, base::State *)
 Select a state along motion and propagate a new motion from there. Return nullptr if no valid motion could be generated starting at the selected state.
 
unsigned int findDurationAndAncestor (Motion *motion, base::State *state, base::State *scratch, Motion *&ancestor) const
 Find the max. duration that the control_ in motion can be applied s.t. the trajectory passes through state. This means that "ancestor" motions with the same control_ are also considered. A pointer to the oldest ancestor with the same control_ is returned. Upon return applying the control ancestor->control_ for duration steps starting from the state ancestor->startState_ should result in the state state.
 
void freeMemory ()
 
- 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.
 
DirectedControlSamplerPtr controlSampler_
 Directed control sampler.
 
const SpaceInformationsiC_
 SpaceInformation convenience pointer.
 
RNG rng_
 
std::vector< Motion * > startMotions_
 Vector holding all of the start states supplied for the problem Each start motion is the root of its own tree of motions.
 
BinaryHeap< Motion *, MotionComparepriorityQueue_
 Priority queue of motions.
 
Cellbsp_ {nullptr}
 Binary Space Partition.
 
base::ProjectionEvaluatorPtr projectionEvaluator_
 Projection evaluator for the problem.
 
double goalBias_ {0.05}
 Number between 0 and 1 specifying the probability with which the goal should be sampled.
 
base::GoalSampleableRegiongoalSampler_ {nullptr}
 Objected used to sample the goal.
 
unsigned int iteration_ {1}
 Iteration number and priority of the next Motion that will be generated.
 
MotionlastGoalMotion_ {nullptr}
 Closest motion to the goal.
 
- 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
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

Path-Directed Subdivision Tree.

Short description
PDST is a tree-based motion planner that attempts to detect the less explored area of the space through the use of a binary space partition of a projection of the state space. Exploration is biased towards large cells with few path segments. Unlike most tree-based planners which expand from a randomly select endpoint of a path segment, PDST expands from a randomly selected point along a deterministically selected path segment. Because of this, it is recommended to increase the min. and max. control duration using ompl::control::SpaceInformation::setMinMaxControlDuration. It is important to set the projection the algorithm uses (setProjectionEvaluator() function). If no projection is set, the planner will attempt to use the default projection associated to the state space. An exception is thrown if no default projection is available either.
External documentation
A.M. Ladd and L.E. Kavraki, Motion planning in the presence of drift, underactuation and discrete system changes, in Robotics: Science and Systems I, pp. 233–241, MIT Press, June 2005. [PDF]

Definition at line 80 of file PDST.h.


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