ompl::base::MaximizeMinClearanceObjective Class Reference

Objective for attempting to maximize the minimum clearance along a path. More...

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

Inheritance diagram for ompl::base::MaximizeMinClearanceObjective:

Public Member Functions

 MaximizeMinClearanceObjective (const SpaceInformationPtr &si)
 
virtual Cost stateCost (const State *s) const
 Defined as the clearance of the state s, which is computed using the StateValidityChecker in this objective's SpaceInformation.
 
virtual bool isCostBetterThan (Cost c1, Cost c2) const
 Since we wish to maximize clearance, and costs are equivalent to path clearance, we return the greater of the two cost values.
 
virtual Cost identityCost () const
 Returns +infinity, since any cost combined with +infinity under this objective will always return the other cost.
 
virtual Cost infiniteCost () const
 Returns -infinity, since no path clearance value can be considered worse than this.
 
- Public Member Functions inherited from ompl::base::MinimaxObjective
 MinimaxObjective (const SpaceInformationPtr &si)
 
virtual Cost motionCost (const State *s1, const State *s2) const
 Interpolates between s1 and s2 to check for state costs along the motion between the two states. Assumes all costs are worse than identity.
 
virtual Cost combineCosts (Cost c1, Cost c2) const
 Since we're only concerned about the "worst" state cost in the path, combining two costs just returns the worse of the two.
 
- Public Member Functions inherited from ompl::base::OptimizationObjective
 OptimizationObjective (const 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.
 
virtual bool isSatisfied (Cost c) const
 Verify that our objective is satisfied already and we can stop planning.
 
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 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 bool isSymmetric () const
 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.
 
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.
 
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 SpaceInformationPtrgetSpaceInformation () const
 Returns this objective's SpaceInformation. Needed for operators in MultiOptimizationObjective.
 

Additional Inherited Members

- 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

Objective for attempting to maximize the minimum clearance along a path.

Definition at line 47 of file MaximizeMinClearanceObjective.h.


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