#include <ompl/base/objectives/VFUpstreamCriterionOptimizationObjective.h>

Inheritance diagram for ompl::base::VFUpstreamCriterionOptimizationObjective:

Public Member Functions
	VFUpstreamCriterionOptimizationObjective (const ompl::base::SpaceInformationPtr &si, geometric::VFRRT::VectorField vf)

bool	isSatisfied (ompl::base::Cost) const override

Cost	stateCost (const State *) const override
	Returns a cost with a value of 0.

ompl::base::Cost	motionCost (const State s1, const State s2) const override

bool	isSymmetric () const override
	Check if this objective has a symmetric cost metric, i.e. motionCost(s1, s2) = motionCost(s2, s1). Default implementation returns whether the underlying state space has symmetric interpolation.

Public Member Functions inherited from ompl::base::OptimizationObjective
	OptimizationObjective (const OptimizationObjective &)=delete

OptimizationObjective &	operator= (const OptimizationObjective &)=delete

	OptimizationObjective (SpaceInformationPtr si)
	Constructor. The objective must always know the space information it is part of. The cost threshold for objective satisfaction defaults to 0.0.

const std::string &	getDescription () const
	Get the description of this optimization objective.

Cost	getCostThreshold () const
	Returns the cost threshold currently being checked for objective satisfaction.

void	setCostThreshold (Cost c)
	Set the cost threshold for objective satisfaction. When a path is found with a cost better than the cost threshold, the objective is considered satisfied.

virtual bool	isCostBetterThan (Cost c1, Cost c2) const
	Check whether the the cost c1 is considered better than the cost c2. By default, this returns true if if c1 is less than c2.

virtual bool	isCostEquivalentTo (Cost c1, Cost c2) const
	Compare whether cost c1 and cost c2 are equivalent. By default defined as !isCostBetterThan(c1, c2) && !isCostBetterThan(c2, c1), as if c1 is not better than c2, and c2 is not better than c1, then they are equal.

virtual bool	isFinite (Cost cost) const
	Returns whether the cost is finite or not.

virtual Cost	betterCost (Cost c1, Cost c2) const
	Return the minimum cost given c1 and c2. Uses isCostBetterThan.

virtual Cost	controlCost (const control::Control *c, unsigned int steps) const
	Get the cost that corresponds to the motion created by a control c applied for duration steps. The default implementation uses the identityCost.

virtual Cost	combineCosts (Cost c1, Cost c2) const
	Get the cost that corresponds to combining the costs c1 and c2. Default implementation defines this combination as an addition.

virtual Cost	identityCost () const
	Get the identity cost value. The identity cost value is the cost c_i such that, for all costs c, combineCosts(c, c_i) = combineCosts(c_i, c) = c. In other words, combining a cost with the identity cost does not change the original cost. By default, a cost with the value 0.0 is returned. It's very important to override this with the proper identity value for your optimization objectives, or else optimal planners may not work.

virtual Cost	infiniteCost () const
	Get a cost which is greater than all other costs in this OptimizationObjective; required for use in Dijkstra/Astar. Defaults to returning the double value inf.

virtual Cost	initialCost (const State *s) const
	Returns a cost value corresponding to starting at a state s. No optimal planners currently support this method. Defaults to returning the objective's identity cost.

virtual Cost	terminalCost (const State *s) const
	Returns a cost value corresponding to a path ending at a state s. No optimal planners currently support this method. Defaults to returning the objective's identity cost.

virtual Cost	averageStateCost (unsigned int numStates) const
	Compute the average state cost of this objective by taking a sample of numStates states.

void	setCostToGoHeuristic (const CostToGoHeuristic &costToGo)
	Set the cost-to-go heuristic function for this objective. The cost-to-go heuristic is a function which returns an admissible estimate of the optimal path cost from a given state to a goal, where "admissible" means that the estimated cost is always less than the true optimal cost.

bool	hasCostToGoHeuristic () const
	Check if this objective has a cost-to-go heuristic function.

Cost	costToGo (const State state, const Goal goal) const
	Uses a cost-to-go heuristic to calculate an admissible estimate of the optimal cost from a given state to a given goal. If no cost-to-go heuristic has been specified with setCostToGoHeuristic(), this function just returns the identity cost, which is sure to be an admissible heuristic if there are no negative costs.

virtual Cost	motionCostHeuristic (const State s1, const State s2) const
	Defines an admissible estimate on the optimal cost on the motion between states s1 and s2. An admissible estimate always undervalues the true optimal cost of the motion. Used by some planners to speed up planning. The default implementation of this method returns this objective's identity cost, which is sure to be an admissible heuristic if there are no negative costs.

const SpaceInformationPtr &	getSpaceInformation () const
	Returns this objective's SpaceInformation. Needed for operators in MultiOptimizationObjective.

virtual InformedSamplerPtr	allocInformedStateSampler (const ProblemDefinitionPtr &probDefn, unsigned int maxNumberCalls) const
	Allocate a heuristic-sampling state generator for this cost function, defaults to a basic rejection sampling scheme when the derived class does not provide a better method.

virtual void	print (std::ostream &out) const
	Print information about this optimization objective.

Protected Attributes
geometric::VFRRT::VectorField	vf_

Protected Attributes inherited from ompl::base::OptimizationObjective
SpaceInformationPtr	si_
	The space information for this objective.

std::string	description_
	The description of this optimization objective.

Cost	threshold_
	The cost threshold used for checking whether this objective has been satisfied during planning.

CostToGoHeuristic	costToGoFn_
	The function used for returning admissible estimates on the optimal cost of the path between a given state and goal.

Detailed Description

Optimization objective that computes the upstream criterion between two states.

Definition at line 116 of file VFUpstreamCriterionOptimizationObjective.h.

Constructor & Destructor Documentation

◆ VFUpstreamCriterionOptimizationObjective()

ompl::base::VFUpstreamCriterionOptimizationObjective::VFUpstreamCriterionOptimizationObjective	(	const ompl::base::SpaceInformationPtr &	si,
		geometric::VFRRT::VectorField	vf
	)