Definition of a problem to be solved. This includes the start state(s) for the system and a goal specification. Will contain solutions, if found. More...

#include <ompl/base/ProblemDefinition.h>

Inheritance diagram for ompl::base::ProblemDefinition:

[legend]

Public Member Functions
	ProblemDefinition (const ProblemDefinition &)=delete
ProblemDefinition &	operator= (const ProblemDefinition &)=delete
	ProblemDefinition (SpaceInformationPtr si)
	Create a problem definition given the SpaceInformation it is part of.
ProblemDefinitionPtr	clone () const
	Return a copy of the problem definition.
const SpaceInformationPtr &	getSpaceInformation () const
	Get the space information this problem definition is for.
void	addStartState (const State *state)
	Add a start state. The state is copied.
void	addStartState (const ScopedState<> &state)
	Add a start state. The state is copied.
bool	hasStartState (const State state, unsigned int startIndex=nullptr) const
	Check whether a specified starting state is already included in the problem definition and optionally return the index of that starting state.
void	clearStartStates ()
	Clear all start states (memory is freed).
unsigned int	getStartStateCount () const
	Returns the number of start states.
const State *	getStartState (unsigned int index) const
	Returns a specific start state.
State *	getStartState (unsigned int index)
	Returns a specific start state.
void	setGoal (const GoalPtr &goal)
	Set the goal.
void	clearGoal ()
	Clear the goal. Memory is freed.
const GoalPtr &	getGoal () const
	Return the current goal.
void	getInputStates (std::vector< const State * > &states) const
	Get all the input states. This includes start states and states that are part of goal regions that can be casted as ompl::base::GoalState or ompl::base::GoalStates.
void	setStartAndGoalStates (const State start, const State goal, double threshold=std::numeric_limits< double >::epsilon())
	In the simplest case possible, we have a single starting state and a single goal state.
void	setGoalState (const State *goal, double threshold=std::numeric_limits< double >::epsilon())
	A simple form of setting the goal. This is called by setStartAndGoalStates(). A more general form is setGoal().
void	setStartAndGoalStates (const ScopedState<> &start, const ScopedState<> &goal, const double threshold=std::numeric_limits< double >::epsilon())
	In the simplest case possible, we have a single starting state and a single goal state.
void	setGoalState (const ScopedState<> &goal, const double threshold=std::numeric_limits< double >::epsilon())
	A simple form of setting the goal. This is called by setStartAndGoalStates(). A more general form is setGoal().
bool	hasOptimizationObjective () const
	Check if an optimization objective was defined for planning.
const OptimizationObjectivePtr &	getOptimizationObjective () const
	Get the optimization objective to be considered during planning.
void	setOptimizationObjective (const OptimizationObjectivePtr &optimizationObjective)
	Set the optimization objective to be considered during planning.
const ReportIntermediateSolutionFn &	getIntermediateSolutionCallback () const
	When this function returns a valid function pointer, that function should be called by planners that compute intermediate solutions every time a better solution is found.
void	setIntermediateSolutionCallback (const ReportIntermediateSolutionFn &callback)
	Set the callback to be called by planners that can compute intermediate solutions.
bool	isTrivial (unsigned int startIndex=nullptr, double distance=nullptr) const
	A problem is trivial if a given starting state already in the goal region, so we need no motion planning. startID will be set to the index of the starting state that satisfies the goal. The distance to the goal can optionally be returned as well.
PathPtr	isStraightLinePathValid () const
	Check if a straight line path is valid. If it is, return an instance of a path that represents the straight line.
bool	fixInvalidInputStates (double distStart, double distGoal, unsigned int attempts)
	Many times the start or goal state will barely touch an obstacle. In this case, we may want to automatically find a nearby state that is valid so motion planning can be performed. This function enables this behaviour. The allowed distance for both start and goal states is specified. The number of attempts is also specified. Returns true if all states are valid after completion.
bool	hasSolution () const
	Returns true if a solution path has been found (could be approximate).
bool	hasExactSolution () const
	Returns true if an exact solution path has been found. Specifically returns hasSolution && !hasApproximateSolution().
bool	hasApproximateSolution () const
	Return true if the top found solution is approximate (does not actually reach the desired goal, but hopefully is closer to it).
double	getSolutionDifference () const
	Get the distance to the desired goal for the top solution. Return -1.0 if there are no solutions available.
bool	hasOptimizedSolution () const
	Return true if the top found solution is optimized (satisfies the specified optimization objective).
PathPtr	getSolutionPath () const
	Return the top solution path, if one is found. The top path is a shortest path that was found, preference being given to solutions that are not approximate.
bool	getSolution (PlannerSolution &solution) const
	Return true if a top solution is found, with the top solution passed by reference in the function header The top path is a shortest path that was found, preference being given to solutions that are not approximate. This will need to be casted into the specialization computed by the planner.
void	addSolutionPath (const PathPtr &path, bool approximate=false, double difference=-1.0, const std::string &plannerName="Unknown") const
	Add a solution path in a thread-safe manner. Multiple solutions can be set for a goal. If a solution does not reach the desired goal it is considered approximate. Optionally, the distance between the desired goal and the one actually achieved is set by difference. Optionally, the name of the planner that generated the solution.
void	addSolutionPath (const PlannerSolution &sol) const
	Add a solution path in a thread-safe manner. Multiple solutions can be set for a goal.
std::size_t	getSolutionCount () const
	Get the number of solutions already found.
std::vector< PlannerSolution >	getSolutions () const
	Get all the solution paths available for this goal.
void	clearSolutionPaths () const
	Forget the solution paths (thread safe). Memory is freed.
bool	hasSolutionNonExistenceProof () const
	Returns true if the problem definition has a proof of non existence for a solution.
void	clearSolutionNonExistenceProof ()
	Removes any existing instance of SolutionNonExistenceProof.
const SolutionNonExistenceProofPtr &	getSolutionNonExistenceProof () const
	Retrieve a pointer to the SolutionNonExistenceProof instance for this problem definition.
void	setSolutionNonExistenceProof (const SolutionNonExistenceProofPtr &nonExistenceProof)
	Set the instance of SolutionNonExistenceProof for this problem definition.
void	print (std::ostream &out=std::cout) const
	Print information about the start and goal states and the optimization objective.

Protected Member Functions
bool	fixInvalidInputState (State *state, double dist, bool start, unsigned int attempts)
	Helper function for fixInvalidInputStates(). Attempts to fix an individual state.

Protected Attributes
SpaceInformationPtr	si_
	The space information this problem definition is for.
std::vector< State * >	startStates_
	The set of start states.
GoalPtr	goal_
	The goal representation.
SolutionNonExistenceProofPtr	nonExistenceProof_
	A Representation of a proof of non-existence of a solution for this problem definition.
OptimizationObjectivePtr	optimizationObjective_
	The objective to be optimized while solving the planning problem.
ReportIntermediateSolutionFn	intermediateSolutionCallback_
	Callback function which is called when a new intermediate solution has been found.

Detailed Description

Definition of a problem to be solved. This includes the start state(s) for the system and a goal specification. Will contain solutions, if found.

Definition at line 151 of file ProblemDefinition.h.

Constructor & Destructor Documentation

◆ ProblemDefinition()

ompl::base::ProblemDefinition::ProblemDefinition ( SpaceInformationPtr si )

Create a problem definition given the SpaceInformation it is part of.

Definition at line 162 of file ProblemDefinition.cpp.

◆ ~ProblemDefinition()

virtual ompl::base::ProblemDefinition::~ProblemDefinition ( )

inlinevirtual

Definition at line 169 of file ProblemDefinition.h.

Member Function Documentation

◆ addSolutionPath() [1/2]

void ompl::base::ProblemDefinition::addSolutionPath	(	const PathPtr &	path,
		bool	approximate = false,
		double	difference = -1.0,
		const std::string &	plannerName = "Unknown" ) const

Add a solution path in a thread-safe manner. Multiple solutions can be set for a goal. If a solution does not reach the desired goal it is considered approximate. Optionally, the distance between the desired goal and the one actually achieved is set by difference. Optionally, the name of the planner that generated the solution.

Definition at line 423 of file ProblemDefinition.cpp.

◆ addSolutionPath() [2/2]

void ompl::base::ProblemDefinition::addSolutionPath ( const PlannerSolution & sol ) const

Add a solution path in a thread-safe manner. Multiple solutions can be set for a goal.

Definition at line 433 of file ProblemDefinition.cpp.

◆ addStartState() [1/2]

void ompl::base::ProblemDefinition::addStartState ( const ScopedState<> & state )

inline

Add a start state. The state is copied.

Definition at line 187 of file ProblemDefinition.h.

◆ addStartState() [2/2]

void ompl::base::ProblemDefinition::addStartState ( const State * state )

inline

Add a start state. The state is copied.

Definition at line 181 of file ProblemDefinition.h.

◆ clearGoal()

void ompl::base::ProblemDefinition::clearGoal ( )

inline

Clear the goal. Memory is freed.

Definition at line 230 of file ProblemDefinition.h.

◆ clearSolutionNonExistenceProof()

void ompl::base::ProblemDefinition::clearSolutionNonExistenceProof ( )

Removes any existing instance of SolutionNonExistenceProof.

Definition at line 489 of file ProblemDefinition.cpp.

◆ clearSolutionPaths()

void ompl::base::ProblemDefinition::clearSolutionPaths ( ) const

Forget the solution paths (thread safe). Memory is freed.

Definition at line 460 of file ProblemDefinition.cpp.

◆ clearStartStates()

void ompl::base::ProblemDefinition::clearStartStates ( )

inline

Clear all start states (memory is freed).

Definition at line 198 of file ProblemDefinition.h.

◆ clone()

ompl::base::ProblemDefinitionPtr ompl::base::ProblemDefinition::clone ( ) const

Return a copy of the problem definition.

A deep copy is made of the start and goal states. A shallow copy is made of shared ptrs. The set of solutions paths and the intermediate solution callback function are not copied.

Definition at line 167 of file ProblemDefinition.cpp.

◆ fixInvalidInputState()

bool ompl::base::ProblemDefinition::fixInvalidInputState	(	State *	state,
		double	dist,
		bool	start,
		unsigned int	attempts )

protected

Helper function for fixInvalidInputStates(). Attempts to fix an individual state.

Definition at line 208 of file ProblemDefinition.cpp.

◆ fixInvalidInputStates()

bool ompl::base::ProblemDefinition::fixInvalidInputStates	(	double	distStart,
		double	distGoal,
		unsigned int	attempts )

Many times the start or goal state will barely touch an obstacle. In this case, we may want to automatically find a nearby state that is valid so motion planning can be performed. This function enables this behaviour. The allowed distance for both start and goal states is specified. The number of attempts is also specified. Returns true if all states are valid after completion.

Definition at line 244 of file ProblemDefinition.cpp.

◆ getGoal()

const GoalPtr & ompl::base::ProblemDefinition::getGoal ( ) const

inline

Return the current goal.

Definition at line 236 of file ProblemDefinition.h.

◆ getInputStates()

void ompl::base::ProblemDefinition::getInputStates ( std::vector< const State * > & states ) const

Get all the input states. This includes start states and states that are part of goal regions that can be casted as ompl::base::GoalState or ompl::base::GoalStates.

Definition at line 273 of file ProblemDefinition.cpp.

◆ getIntermediateSolutionCallback()

const ReportIntermediateSolutionFn & ompl::base::ProblemDefinition::getIntermediateSolutionCallback ( ) const

inline

When this function returns a valid function pointer, that function should be called by planners that compute intermediate solutions every time a better solution is found.

Definition at line 295 of file ProblemDefinition.h.

◆ getOptimizationObjective()

const OptimizationObjectivePtr & ompl::base::ProblemDefinition::getOptimizationObjective ( ) const

inline

Get the optimization objective to be considered during planning.

Definition at line 282 of file ProblemDefinition.h.

◆ getSolution()

bool ompl::base::ProblemDefinition::getSolution ( PlannerSolution & solution ) const

Return true if a top solution is found, with the top solution passed by reference in the function header The top path is a shortest path that was found, preference being given to solutions that are not approximate. This will need to be casted into the specialization computed by the planner.

Definition at line 418 of file ProblemDefinition.cpp.

◆ getSolutionCount()

std::size_t ompl::base::ProblemDefinition::getSolutionCount ( ) const

Get the number of solutions already found.

Definition at line 408 of file ProblemDefinition.cpp.

◆ getSolutionDifference()

double ompl::base::ProblemDefinition::getSolutionDifference ( ) const

Get the distance to the desired goal for the top solution. Return -1.0 if there are no solutions available.

Definition at line 450 of file ProblemDefinition.cpp.

◆ getSolutionNonExistenceProof()

const ompl::base::SolutionNonExistenceProofPtr & ompl::base::ProblemDefinition::getSolutionNonExistenceProof ( ) const

Retrieve a pointer to the SolutionNonExistenceProof instance for this problem definition.

Definition at line 494 of file ProblemDefinition.cpp.

◆ getSolutionPath()

ompl::base::PathPtr ompl::base::ProblemDefinition::getSolutionPath ( ) const

Return the top solution path, if one is found. The top path is a shortest path that was found, preference being given to solutions that are not approximate.

This will need to be casted into the specialization computed by the planner

Definition at line 413 of file ProblemDefinition.cpp.

◆ getSolutions()

std::vector< ompl::base::PlannerSolution > ompl::base::ProblemDefinition::getSolutions ( ) const

Get all the solution paths available for this goal.

Definition at line 455 of file ProblemDefinition.cpp.

◆ getSpaceInformation()

const SpaceInformationPtr & ompl::base::ProblemDefinition::getSpaceInformation ( ) const

inline

Get the space information this problem definition is for.

Definition at line 175 of file ProblemDefinition.h.

◆ getStartState() [1/2]

State * ompl::base::ProblemDefinition::getStartState ( unsigned int index )

inline

Returns a specific start state.

Definition at line 218 of file ProblemDefinition.h.

◆ getStartState() [2/2]

const State * ompl::base::ProblemDefinition::getStartState ( unsigned int index ) const

inline

Returns a specific start state.

Definition at line 212 of file ProblemDefinition.h.

◆ getStartStateCount()

unsigned int ompl::base::ProblemDefinition::getStartStateCount ( ) const

inline

Returns the number of start states.

Definition at line 206 of file ProblemDefinition.h.

◆ hasApproximateSolution()

bool ompl::base::ProblemDefinition::hasApproximateSolution ( ) const

Return true if the top found solution is approximate (does not actually reach the desired goal, but hopefully is closer to it).

Definition at line 440 of file ProblemDefinition.cpp.

◆ hasExactSolution()

bool ompl::base::ProblemDefinition::hasExactSolution ( ) const

inline

Returns true if an exact solution path has been found. Specifically returns hasSolution && !hasApproximateSolution().

Definition at line 340 of file ProblemDefinition.h.

◆ hasOptimizationObjective()

bool ompl::base::ProblemDefinition::hasOptimizationObjective ( ) const

inline

Check if an optimization objective was defined for planning.

Definition at line 276 of file ProblemDefinition.h.

◆ hasOptimizedSolution()

bool ompl::base::ProblemDefinition::hasOptimizedSolution ( ) const

Return true if the top found solution is optimized (satisfies the specified optimization objective).

Definition at line 445 of file ProblemDefinition.cpp.

◆ hasSolution()

bool ompl::base::ProblemDefinition::hasSolution ( ) const

Returns true if a solution path has been found (could be approximate).

Definition at line 403 of file ProblemDefinition.cpp.

◆ hasSolutionNonExistenceProof()

bool ompl::base::ProblemDefinition::hasSolutionNonExistenceProof ( ) const

Returns true if the problem definition has a proof of non existence for a solution.

Definition at line 484 of file ProblemDefinition.cpp.

◆ hasStartState()

bool ompl::base::ProblemDefinition::hasStartState	(	const State *	state,
		unsigned int *	startIndex = nullptr ) const

Check whether a specified starting state is already included in the problem definition and optionally return the index of that starting state.

Definition at line 196 of file ProblemDefinition.cpp.

◆ isStraightLinePathValid()

ompl::base::PathPtr ompl::base::ProblemDefinition::isStraightLinePathValid ( ) const

Check if a straight line path is valid. If it is, return an instance of a path that represents the straight line.

Note: When planning under geometric constraints, this works only if the goal region can be sampled. If the goal region cannot be sampled, this call is equivalent to calling isTrivial(); When planning under differential constraints, the system is propagated forward in time using the null control.

Definition at line 289 of file ProblemDefinition.cpp.

◆ isTrivial()

bool ompl::base::ProblemDefinition::isTrivial	(	unsigned int *	startIndex = nullptr,
		double *	distance = nullptr ) const

A problem is trivial if a given starting state already in the goal region, so we need no motion planning. startID will be set to the index of the starting state that satisfies the goal. The distance to the goal can optionally be returned as well.

Definition at line 371 of file ProblemDefinition.cpp.

◆ print()

void ompl::base::ProblemDefinition::print ( std::ostream & out = std::cout ) const

Print information about the start and goal states and the optimization objective.

Definition at line 465 of file ProblemDefinition.cpp.

◆ setGoal()

void ompl::base::ProblemDefinition::setGoal ( const GoalPtr & goal )

inline

Set the goal.

Definition at line 224 of file ProblemDefinition.h.

◆ setGoalState() [1/2]

void ompl::base::ProblemDefinition::setGoalState	(	const ScopedState<> &	goal,
		const double	threshold = std::numeric_limits<double>::epsilon() )

inline

A simple form of setting the goal. This is called by setStartAndGoalStates(). A more general form is setGoal().

Definition at line 269 of file ProblemDefinition.h.

◆ setGoalState() [2/2]

void ompl::base::ProblemDefinition::setGoalState	(	const State *	goal,
		double	threshold = std::numeric_limits<double>::epsilon() )

A simple form of setting the goal. This is called by setStartAndGoalStates(). A more general form is setGoal().

Definition at line 187 of file ProblemDefinition.cpp.

◆ setIntermediateSolutionCallback()

void ompl::base::ProblemDefinition::setIntermediateSolutionCallback ( const ReportIntermediateSolutionFn & callback )

inline

Set the callback to be called by planners that can compute intermediate solutions.

Definition at line 301 of file ProblemDefinition.h.

◆ setOptimizationObjective()

void ompl::base::ProblemDefinition::setOptimizationObjective ( const OptimizationObjectivePtr & optimizationObjective )

inline

Set the optimization objective to be considered during planning.

Definition at line 288 of file ProblemDefinition.h.

◆ setSolutionNonExistenceProof()

void ompl::base::ProblemDefinition::setSolutionNonExistenceProof ( const SolutionNonExistenceProofPtr & nonExistenceProof )

Set the instance of SolutionNonExistenceProof for this problem definition.

Definition at line 499 of file ProblemDefinition.cpp.

◆ setStartAndGoalStates() [1/2]

void ompl::base::ProblemDefinition::setStartAndGoalStates	(	const ScopedState<> &	start,
		const ScopedState<> &	goal,
		const double	threshold = std::numeric_limits<double>::epsilon() )

inline

In the simplest case possible, we have a single starting state and a single goal state.

This function simply configures the problem definition using these states (performs the needed calls to addStartState(), creates an instance of ompl::base::GoalState and calls setGoal() on it.

Definition at line 262 of file ProblemDefinition.h.

◆ setStartAndGoalStates() [2/2]

void ompl::base::ProblemDefinition::setStartAndGoalStates	(	const State *	start,
		const State *	goal,
		double	threshold = std::numeric_limits<double>::epsilon() )

In the simplest case possible, we have a single starting state and a single goal state.

This function simply configures the problem definition using these states (performs the needed calls to addStartState(), creates an instance of ompl::base::GoalState and calls setGoal() on it.

Definition at line 180 of file ProblemDefinition.cpp.

Member Data Documentation

◆ goal_

GoalPtr ompl::base::ProblemDefinition::goal_

protected

The goal representation.

Definition at line 417 of file ProblemDefinition.h.

◆ intermediateSolutionCallback_

ReportIntermediateSolutionFn ompl::base::ProblemDefinition::intermediateSolutionCallback_

protected

Callback function which is called when a new intermediate solution has been found.

Definition at line 426 of file ProblemDefinition.h.

◆ nonExistenceProof_

SolutionNonExistenceProofPtr ompl::base::ProblemDefinition::nonExistenceProof_

protected

A Representation of a proof of non-existence of a solution for this problem definition.

Definition at line 420 of file ProblemDefinition.h.

◆ optimizationObjective_

OptimizationObjectivePtr ompl::base::ProblemDefinition::optimizationObjective_

protected

The objective to be optimized while solving the planning problem.

Definition at line 423 of file ProblemDefinition.h.

◆ si_

SpaceInformationPtr ompl::base::ProblemDefinition::si_

protected

The space information this problem definition is for.

Definition at line 411 of file ProblemDefinition.h.

◆ startStates_

std::vector<State *> ompl::base::ProblemDefinition::startStates_

protected

The set of start states.

Definition at line 414 of file ProblemDefinition.h.

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

ompl/base/ProblemDefinition.h
ompl/base/src/ProblemDefinition.cpp

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ProblemDefinition()

◆ ~ProblemDefinition()

Member Function Documentation

◆ addSolutionPath() [1/2]

◆ addSolutionPath() [2/2]

◆ addStartState() [1/2]

◆ addStartState() [2/2]

◆ clearGoal()

◆ clearSolutionNonExistenceProof()

◆ clearSolutionPaths()

◆ clearStartStates()

◆ clone()

◆ fixInvalidInputState()

◆ fixInvalidInputStates()

◆ getGoal()

◆ getInputStates()

◆ getIntermediateSolutionCallback()

◆ getOptimizationObjective()

◆ getSolution()

◆ getSolutionCount()

◆ getSolutionDifference()

◆ getSolutionNonExistenceProof()

◆ getSolutionPath()

◆ getSolutions()

◆ getSpaceInformation()

◆ getStartState() [1/2]

◆ getStartState() [2/2]

◆ getStartStateCount()

◆ hasApproximateSolution()

◆ hasExactSolution()

◆ hasOptimizationObjective()

◆ hasOptimizedSolution()

◆ hasSolution()

◆ hasSolutionNonExistenceProof()

◆ hasStartState()

◆ isStraightLinePathValid()

◆ isTrivial()

◆ print()

◆ setGoal()

◆ setGoalState() [1/2]

◆ setGoalState() [2/2]

◆ setIntermediateSolutionCallback()

◆ setOptimizationObjective()

◆ setSolutionNonExistenceProof()

◆ setStartAndGoalStates() [1/2]

◆ setStartAndGoalStates() [2/2]

Member Data Documentation

◆ goal_

◆ intermediateSolutionCallback_

◆ nonExistenceProof_

◆ optimizationObjective_

◆ si_

◆ startStates_