Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
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KoulesControlSampler
KoulesControlSpace
KoulesDirectedControlSampler
KoulesGoal
KoulesProjection
KoulesSimulator
KoulesStatePropagator
MyArbitraryGoal
MyClass
MyGoalRegion
MyProjection
ompl
base::AllValidStateValidityCheckerThe simplest state validity checker: all states are valid
ompl::base::CForestStateSamplerExtended state sampler to use with the CForest planning algorithm. It wraps the user-specified state sampler
ompl::base::CForestStateSpaceWrapperState space wrapper to use together with CForest. It adds some functionalities to the regular state spaces necessary to CForest
base::CompoundStateDefinition of a compound state
base::CompoundStateSamplerDefinition of a compound state sampler. This is useful to construct samplers for compound states
base::CompoundStateSpaceA space to allow the composition of state spaces
base::CostDefinition of a cost value. Can represent the cost of a motion or the cost of a state
base::DiscreteMotionValidatorA motion validator that only uses the state validity checker. Motions are checked for validity at a specified resolution
base::DiscreteStateSamplerState space sampler for discrete states
base::DiscreteStateSpaceA space representing discrete states; i.e. there are a small number of discrete states the system can be in. States are represented as integers [lowerBound, upperBound], where lowerBound and upperBound are inclusive. States do not wrap around; i.e. the distance between state lowerBound and state upperBound is upperBound-lowerBound. The dimension of the space is 1
base::DiscreteStateSpace::StateTypeThe definition of a discrete state
base::DubinsMotionValidatorA Dubins motion validator that only uses the state validity checker. Motions are checked for validity at a specified resolution
base::DubinsStateSpaceAn SE(2) state space where distance is measured by the length of Dubins curves
base::DubinsStateSpace::DubinsPathComplete description of a Dubins path
base::GaussianValidStateSamplerGenerate valid samples using the Gaussian sampling strategy
base::GenericParamMotion planning algorithms often employ parameters to guide their exploration process. (e.g., goal biasing). Motion planners (and some of their components) use this class to declare what the parameters are, in a generic way, so that they can be set externally
base::GoalAbstract definition of goals
base::GoalLazySamplesDefinition of a goal region that can be sampled, but the sampling process can be slow. This class allows sampling the happen in a separate thread, and the number of goals may increase, as the planner is running, in a thread-safe manner
ompl::base::GoalPtrA boost shared pointer wrapper for ompl::base::Goal
base::GoalRegionDefinition of a goal region
base::GoalSampleableRegionAbstract definition of a goal region that can be sampled
base::GoalStateDefinition of a goal state
base::GoalStatesDefinition of a set of goal states
base::MaximizeClearanceValidStateSamplerGenerate valid samples randomly, but with a bias towards higher clearance
base::MaximizeMinClearanceObjectiveObjective for attempting to maximize the minimum clearance along a path
base::MechanicalWorkOptimizationObjectiveAn optimization objective which defines path cost using the idea of mechanical work. To be used in conjunction with TRRT
base::MinimaxObjectiveThe cost of a path is defined as the worst state cost over the entire path. This objective attempts to find the path with the "best worst cost" over all paths
ompl::base::MorseEnvironmentThis class contains the MORSE constructs OMPL needs to know about when planning
ompl::base::MorseEnvironmentPtrA boost shared pointer wrapper for ompl::base::MorseEnvironment
ompl::base::MorseGoalThis is a goal class that is more amenable to Python
ompl::base::MorseProjectionThis class implements a generic projection for the MorseStateSpace, namely, the subspace representing the x and y positions of every rigid body
ompl::base::MorseStateSpaceState space representing MORSE states
ompl::base::MorseStateSpace::StateTypeMORSE State. This is a compound state that allows accessing the properties of the bodies the state space is constructed for
ompl::base::MorseStateValidityCheckerThe simplest state validity checker: all states are valid if they are within bounds
ompl::base::MorseTerminationConditionThis class represents a termination condition for the planner that only terminates if the user shuts down the MORSE simulation
base::MotionValidatorAbstract definition for a class checking the validity of motions -- path segments between states. This is often called a local planner. The implementation of this class must be thread safe
ompl::base::MotionValidatorPtrA boost shared pointer wrapper for ompl::base::MotionValidator
base::MultiOptimizationObjectiveThis class allows for the definition of multiobjective optimal planning problems. Objectives are added to this compound object, and motion costs are computed by taking a weighted sum of the individual objective costs
base::MultiOptimizationObjective::ComponentDefines a pairing of an objective and its weight
base::ObstacleBasedValidStateSamplerGenerate valid samples using obstacle based sampling. First sample an invalid state, then sample a valid state. Then, interpolate from the invalid state to the valid state, returning the first valid state encountered
base::OptimizationObjectiveAbstract definition of optimization objectives
ompl::base::OptimizationObjectivePtrA boost shared pointer wrapper for ompl::base::OptimizationObjective
base::ParamSetMaintain a set of parameters
base::PathAbstract definition of a path
base::PathLengthOptimizationObjectiveAn optimization objective which corresponds to optimizing path length
ompl::base::PathPtrA boost shared pointer wrapper for ompl::base::Path
base::PlannerBase class for a planner
base::PlannerDataObject containing planner generated vertex and edge data. It is assumed that all vertices are unique, and only a single directed edge connects two vertices
base::PlannerData::GraphWrapper class for the Boost.Graph representation of the PlannerData. This class inherits from a boost::adjacency_list Graph structure
base::PlannerDataEdgeBase class for a PlannerData edge
ompl::base::PlannerDataPtrA boost shared pointer wrapper for ompl::base::PlannerData
base::PlannerDataStorageObject that handles loading/storing a PlannerData object to/from a binary stream. Serialization of vertices and edges is performed using the Boost archive method serialize. Derived vertex/edge classes are handled, presuming those classes implement the serialize method
base::PlannerDataStorage::HeaderInformation stored at the beginning of the PlannerData archive
base::PlannerDataStorage::PlannerDataEdgeDataThe object containing all edge data that will be stored
base::PlannerDataStorage::PlannerDataVertexDataThe object containing all vertex data that will be stored
base::PlannerDataVertexBase class for a vertex in the PlannerData structure. All derived classes must implement the clone and equivalence operators. It is assumed that each vertex in the PlannerData structure is unique (i.e. no duplicates allowed)
base::PlannerInputStatesHelper class to extract valid start & goal states. Usually used internally by planners
ompl::base::PlannerPtrA boost shared pointer wrapper for ompl::base::Planner
base::PlannerSolutionRepresentation of a solution to a planning problem
base::PlannerSpecsProperties that planners may have
base::PlannerStatusA class to store the exit status of Planner::solve()
base::PlannerTerminationConditionEncapsulate a termination condition for a motion planner. Planners will call operator() to decide whether they should terminate before a solution is found or not. operator() will return true if either the implemented condition is met (the call to eval() returns true) or if the user called terminate(true)
base::PrecomputedStateSamplerState space sampler for discrete states
base::ProblemDefinitionDefinition of a problem to be solved. This includes the start state(s) for the system and a goal specification. Will contain solutions, if found
ompl::base::ProblemDefinitionPtrA boost shared pointer wrapper for ompl::base::ProblemDefinition
base::ProjectionEvaluatorAbstract definition for a class computing projections to Rn. Implicit integer grids are imposed on this projection space by setting cell sizes. Before use, the user must supply cell sizes for the integer grid (setCellSizes()). The implementation of this class is thread safe
ompl::base::ProjectionEvaluatorPtrA boost shared pointer wrapper for ompl::base::ProjectionEvaluator
base::ProjectionMatrixA projection matrix -- it allows multiplication of real vectors by a specified matrix. The matrix can also be randomly generated
base::RealVectorBoundsThe lower and upper bounds for an Rn space
base::RealVectorIdentityProjectionEvaluatorDefine the identity projection
base::RealVectorLinearProjectionEvaluatorDefinition for a class computing linear projections (multiplication of a k-by-n matrix to the the Rn vector state to produce an Rk projection. The multiplication matrix needs to be supplied as input
base::RealVectorOrthogonalProjectionEvaluatorDefinition for a class computing orthogonal projections
base::RealVectorRandomLinearProjectionEvaluatorDefinition for a class computing a random linear projections
base::RealVectorStateSamplerState sampler for the Rn state space
base::RealVectorStateSpaceA state space representing Rn. The distance function is the L2 norm
base::RealVectorStateSpace::StateTypeThe definition of a state in Rn
base::ReedsSheppMotionValidatorA Reeds-Shepp motion validator that only uses the state validity checker. Motions are checked for validity at a specified resolution
base::ReedsSheppStateSpaceAn SE(2) state space where distance is measured by the length of Reeds-Shepp curves
base::ReedsSheppStateSpace::ReedsSheppPathComplete description of a ReedsShepp path
base::SamplerSelector< T >Depending on the type of state sampler, we have different allocation routines
base::ScopedState< T >Definition of a scoped state
base::SE2StateSpaceA state space representing SE(2)
base::SE2StateSpace::StateTypeA state in SE(2): (x, y, yaw)
base::SE3StateSpaceA state space representing SE(3)
base::SE3StateSpace::StateTypeA state in SE(3): position = (x, y, z), quaternion = (x, y, z, w)
base::SO2StateSamplerState space sampler for SO(2)
base::SO2StateSpaceA state space representing SO(2). The distance function and interpolation take into account angle wrapping
base::SO2StateSpace::StateTypeThe definition of a state in SO(2)
base::SO3StateSamplerState space sampler for SO(3), using quaternion representation
base::SO3StateSpaceA state space representing SO(3). The internal representation is done with quaternions. The distance between states is the angle between quaternions and interpolation is done with slerp
base::SO3StateSpace::StateTypeThe definition of a state in SO(3) represented as a unit quaternion
base::SolutionNonExistenceProofAbstract definition of a proof for the non-existence of a solution to a problem
ompl::base::SolutionNonExistenceProofPtrA boost shared pointer wrapper for ompl::base::SolutionNonExistenceProof
base::SpaceInformationThe base class for space information. This contains all the information about the space planning is done in. setup() needs to be called as well, before use
ompl::base::SpaceInformationPtrA boost shared pointer wrapper for ompl::base::SpaceInformation
base::SpecificParam< T >This is a helper class that instantiates parameters with different data types
base::StateDefinition of an abstract state
base::StateCostIntegralObjectiveDefines optimization objectives where path cost can be represented as a path integral over a cost function defined over the state space. This cost function is specified by implementing the stateCost() method
ompl::base::StatePropagatorPtrA boost shared pointer wrapper for ompl::control::StatePropagator
base::StateSamplerAbstract definition of a state space sampler
base::StateSamplerArray< T >Class to ease the creation of a set of samplers. This is especially useful for multi-threaded planners
ompl::base::StateSamplerPtrA boost shared pointer wrapper for ompl::base::StateSampler
base::StateSpaceRepresentation of a space in which planning can be performed. Topology specific sampling, interpolation and distance are defined
base::StateSpace::SubstateLocationRepresentation of the address of a substate in a state. This structure stores the indexing information needed to access a particular substate of a state
base::StateSpace::ValueLocationRepresentation of the address of a value in a state. This structure stores the indexing information needed to access elements of a state (no pointer values are stored)
ompl::base::StateSpacePtrA boost shared pointer wrapper for ompl::base::StateSpace
base::StateStorageManage loading and storing for a set of states of a specified state space
base::StateStorage::HeaderInformation stored at the beginning of the archive
base::StateStorageWithMetadata< M >State storage that allows storing state metadata as well
base::StateValidityCheckerAbstract definition for a class checking the validity of states. The implementation of this class must be thread safe
ompl::base::StateValidityCheckerPtrA boost shared pointer wrapper for ompl::base::StateValidityChecker
base::StateValidityCheckerSpecsProperties that a state validity checker may have
base::SubspaceProjectionEvaluatorIf the projection for a CompoundStateSpace is supposed to be the same as the one for one of its included subspaces, this class facilitates selecting a projection of that subspace
base::SubspaceStateSamplerConstruct a sampler that samples only within a subspace of the space
base::TimeStateSamplerState space sampler for time
base::TimeStateSpaceA state space representing time. The time can be unbounded, in which case enforceBounds() is a no-op, satisfiesBounds() always returns true, sampling uniform time states always produces time 0 and getMaximumExtent() returns 1. If time is bounded (setBounds() has been previously called), the state space behaves as expected. After construction, the state space is unbounded. isBounded() can be used to check if the state space is bounded or not
base::TimeStateSpace::StateTypeThe definition of a time state
base::UniformValidStateSamplerA state sampler that only samples valid states, uniformly
base::ValidStateSamplerAbstract definition of a state sampler
ompl::base::ValidStateSamplerPtrA boost shared pointer wrapper for ompl::base::ValidStateSampler
ompl::BinaryHeap< _T, LessThan >This class provides an implementation of an updatable min-heap. Using it is a bit cumbersome, as it requires keeping track of the BinaryHeap::Element* type, however, it should be as fast as it gets with an updatable heap
ompl::BinaryHeap< _T, LessThan >::ElementWhen an element is added to the heap, an instance of Element* is created. This instance contains the data that was added and internal information about the position of the data in the heap's internal storage
ompl::control::AutomatonA class to represent a deterministic finite automaton, each edge of which corresponds to a World. A system trajectory, by way of project() and worldAtRegion() in PropositionalDecomposition, determines a sequence of Worlds, which are read by an Automaton to determine whether a trajectory satisfies a given specification
ompl::control::Automaton::TransitionMapEach automaton state has a transition map, which maps from a World to another automaton state. A set $P$ of true propositions correponds to the formula $\bigwedge_{p\in P} p$
ompl::control::AutomatonPtrA boost shared pointer wrapper for ompl::control::Automaton
ompl::control::CompoundControlDefinition of a compound control
ompl::control::CompoundControlSamplerDefinition of a compound control sampler. This is useful to construct samplers for compound controls
ompl::control::CompoundControlSpaceA control space to allow the composition of control spaces
ompl::control::ControlDefinition of an abstract control
ompl::control::ControlSamplerAbstract definition of a control sampler. Motion planners that need to sample controls will call functions from this class. Planners should call the versions of sample() and sampleNext() with most arguments, whenever this information is available
ompl::control::ControlSamplerPtrA boost shared pointer wrapper for ompl::control::ControlSampler
ompl::control::ControlSpaceA control space representing the space of applicable controls
ompl::control::ControlSpacePtrA boost shared pointer wrapper for ompl::control::ControlSpace
ompl::control::DecompositionA Decomposition is a partition of a bounded Euclidean space into a fixed number of regions which are denoted by integers
ompl::control::DecompositionPtrA boost shared pointer wrapper for ompl::control::Decomposition
ompl::control::DirectedControlSamplerAbstract definition of a directed control sampler. Motion planners that need to sample controls that take the system to a desired direction will call functions from this class. Planners should call the versions of sampleTo() with most arguments, whenever this information is available. If no direction information is available, the use of a ControlSampler is perhaps more appropriate
ompl::control::DirectedControlSamplerPtrA boost shared pointer wrapper for ompl::control::DirectedControlSampler
ompl::control::DiscreteControlSamplerControl space sampler for discrete controls
ompl::control::DiscreteControlSpaceA space representing discrete controls; i.e. there are a small number of discrete controls the system can react to. Controls are represented as integers [lowerBound, upperBound], where lowerBound and upperBound are inclusive
ompl::control::DiscreteControlSpace::ControlTypeThe definition of a discrete control
ompl::control::ESTExpansive Space Trees
ompl::control::EST::MotionRepresentation of a motion
ompl::control::EST::MotionInfoA struct containing an array of motions and a corresponding PDF element
ompl::control::EST::TreeDataThe data contained by a tree of exploration
ompl::control::GridDecompositionA GridDecomposition is a Decomposition implemented using a grid
ompl::control::KPIECE1Kinodynamic Planning by Interior-Exterior Cell Exploration
ompl::control::KPIECE1::CellDataThe data held by a cell in the grid of motions
ompl::control::KPIECE1::CloseSampleInformation about a known good sample (closer to the goal than others)
ompl::control::KPIECE1::CloseSamplesBounded set of good samples
ompl::control::KPIECE1::MotionRepresentation of a motion for this algorithm
ompl::control::KPIECE1::OrderCellsByImportanceDefinintion of an operator passed to the Grid structure, to order cells by importance
ompl::control::KPIECE1::TreeDataThe data defining a tree of motions for this algorithm
ompl::control::LTLPlannerA planner for generating system trajectories to satisfy a logical specification given by an automaton, the propositions of which are defined over a decomposition of the system's state space
ompl::control::LTLPlanner::MotionRepresentation of a motion
ompl::control::LTLPlanner::ProductGraphStateInfoA structure to hold measurement information for a high-level state, as well as the set of tree motions belonging to that high-level state. Exactly one ProductGraphStateInfo will exist for each ProductGraph::State
ompl::control::LTLProblemDefinition
ompl::control::LTLProblemDefinitionPtrA boost shared pointer wrapper for ompl::control::LTLProblemDefinition
ompl::control::LTLSpaceInformation
ompl::control::LTLSpaceInformationPtrA boost shared pointer wrapper for ompl::control::LTLSpaceInformation
ompl::control::MorseControlSpaceRepresentation of controls applied in MORSE environments. This is an array of double values
ompl::control::MorseSimpleSetupCreate the set of classes typically needed to solve a control problem when forward propagation is computed with MORSE
ompl::control::MorseStatePropagatorState propagation with MORSE. Only forward propagation is possible
ompl::control::ODEAdaptiveSolver< Solver >Adaptive step size solver for ordinary differential equations of the type q' = f(q, u), where q is the current state of the system and u is a control applied to the system. The maximum integration error is bounded in this approach. Solver is the numerical integration method used to solve the equations, and must implement the error stepper concept from boost::numeric::odeint. The default is a fifth order Runge-Kutta Cash-Karp method with a fourth order error bound
ompl::control::ODEBasicSolver< Solver >Basic solver for ordinary differential equations of the type q' = f(q, u), where q is the current state of the system and u is a control applied to the system. StateType defines the container object describing the state of the system. Solver is the numerical integration method used to solve the equations. The default is a fourth order Runge-Kutta method. This class wraps around the simple stepper concept from boost::numeric::odeint
ompl::control::ODEErrorSolver< Solver >Solver for ordinary differential equations of the type q' = f(q, u), where q is the current state of the system and u is a control applied to the system. StateType defines the container object describing the state of the system. Solver is the numerical integration method used to solve the equations. The default is a fifth order Runge-Kutta Cash-Karp method with a fourth order error bound. This class wraps around the error stepper concept from boost::numeric::odeint
ompl::control::ODESolverAbstract base class for an object that can solve ordinary differential equations (ODE) of the type q' = f(q,u) using numerical integration. Classes deriving from this must implement the solve method. The user must supply the ODE to solve
ompl::control::ODESolverPtrA boost shared pointer wrapper for ompl::control::ODESolver
ompl::control::OpenDEControlSpaceRepresentation of controls applied in OpenDE environments. This is an array of double values
ompl::control::OpenDEEnvironmentThis class contains the OpenDE constructs OMPL needs to know about when planning
ompl::control::OpenDEEnvironmentPtrA boost shared pointer wrapper for ompl::control::OpenDEEnvironment
ompl::control::OpenDESimpleSetupCreate the set of classes typically needed to solve a control problem when forward propagation is computed with OpenDE
ompl::control::OpenDEStatePropagatorState propagation with OpenDE. Only forward propagation is possible
ompl::control::OpenDEStateSpaceState space representing OpenDE states
ompl::control::OpenDEStateSpace::StateTypeOpenDE State. This is a compound state that allows accessing the properties of the bodies the state space is constructed for
ompl::control::OpenDEStateValidityCheckerThe simplest state validity checker: all states are valid
ompl::control::PathControlDefinition of a control path
ompl::control::PDSTPath-Directed Subdivision Tree
ompl::control::PDST::CellCell is a Binary Space Partition
ompl::control::PDST::MotionClass representing the tree of motions exploring the state space
ompl::control::PDST::MotionCompareComparator used to order motions in the priority queue
ompl::control::PlannerDataThis class assumes edges are derived from PlannerDataEdgeControl. If this is not the case, see base::PlannerData
ompl::control::PlannerDataEdgeControlRepresentation of an edge in PlannerData for planning with controls. This structure encodes a specific control and a duration to apply the control
ompl::control::PlannerDataStorageIt is assumed that the edges in stored/loaded PlannerData can be cast to PlannerDataEdgeControl in this class. If this is not the case, see ompl::base::PlannerDataStorage
ompl::control::ProductGraphA ProductGraph represents the weighted, directed, graph-based Cartesian product of a PropositionalDecomposition object, an Automaton corresponding to a co-safe LTL specification, and an Automaton corresponding to a safe LTL specification
ompl::control::ProductGraph::Edge
ompl::control::ProductGraph::StateA State of a ProductGraph represents a vertex in the graph-based Cartesian product represented by the ProductGraph. A State is simply a tuple consisting of a PropositionalDecomposition region, a co-safe Automaton state, and a safe Automaton state
ompl::control::ProductGraphPtrA boost shared pointer wrapper for ompl::control::ProductGraph
ompl::control::PropositionalDecompositionA propositional decomposition wraps a given Decomposition with a region-to-proposition assignment operator. Each region in the decomposition has a corresponding World
ompl::control::PropositionalDecompositionPtrA boost shared pointer wrapper for ompl::control::PropositionalDecomposition
ompl::control::PropositionalTriangularDecompositionA PropositionalTriangularDecomposition is a triangulation that ignores obstacles and respects propositional regions of interest. Practically speaking, it is both a TriangularDecomposition and a PropositionalDecomposition, but it is implemented without using multiple inheritance
ompl::control::RealVectorControlSpaceA control space representing Rn
ompl::control::RealVectorControlSpace::ControlTypeThe definition of a control in Rn
ompl::control::RealVectorControlUniformSamplerUniform sampler for the Rn state space
ompl::control::RRTRapidly-exploring Random Tree
ompl::control::RRT::MotionRepresentation of a motion
ompl::control::SimpleDirectedControlSamplerImplementation of a simple directed control sampler. This is a basic implementation that does not actually take direction into account and builds upon ControlSampler. Instead, a set of k random controls are sampled, and the control that gets the system closest to the target state is returned
ompl::control::SimpleSetupCreate the set of classes typically needed to solve a control problem
ompl::control::SimpleSetupPtrA boost shared pointer wrapper for ompl::control::SimpleSetup
ompl::control::SpaceInformationSpace information containing necessary information for planning with controls. setup() needs to be called before use
ompl::control::SpaceInformationPtrA boost shared pointer wrapper for ompl::control::SpaceInformation
ompl::control::StatePropagatorModel the effect of controls on system states
ompl::control::SteeredControlSamplerAbstract definition of a steered control sampler. It uses the steering function in a state propagator to find the controls that drive from one state to another
ompl::control::SyclopSynergistic Combination of Layers of Planning
ompl::control::Syclop::AdjacencyRepresentation of an adjacency (a directed edge) between two regions in the Decomposition assigned to Syclop
ompl::control::Syclop::DefaultsContains default values for Syclop parameters
ompl::control::Syclop::MotionRepresentation of a motion
ompl::control::Syclop::RegionRepresentation of a region in the Decomposition assigned to Syclop
ompl::control::SyclopESTSyclopEST is Syclop with EST as its low-level tree planner
ompl::control::SyclopRRTSyclopRRT is Syclop with RRT as its low-level tree planner
ompl::control::TriangularDecompositionA TriangularDecomposition is a triangulation that ignores obstacles
ompl::control::TriangularDecomposition::Polygon
ompl::control::TriangularDecomposition::Triangle
ompl::control::TriangularDecomposition::Vertex
ompl::control::WorldA class to represent an assignment of boolean values to propositions. A World can be partially restrictive, i.e., some propositions do not have to be assigned a value, in which case it can take on any value. Our notion of a World is similar to a set of truth assignments in propositional logic
ompl::ExceptionThe exception type for ompl
ompl::FLANNDistance< _T >Wrapper class to allow FLANN access to the NearestNeighbors::distFun_ callback function
ompl::geometric::AnytimePathShortening
ompl::geometric::BKPIECE1Bi-directional KPIECE with one level of discretization
ompl::geometric::BKPIECE1::MotionRepresentation of a motion for this algorithm
ompl::geometric::CForestCoupled Forest of Random Engrafting Search Trees
ompl::geometric::Discretization< Motion >One-level discretization used for KPIECE
ompl::geometric::Discretization< Motion >::CellDataThe data held by a cell in the grid of motions
ompl::geometric::Discretization< Motion >::OrderCellsByImportanceDefinintion of an operator passed to the Grid structure, to order cells by importance
ompl::geometric::ESTExpansive Space Trees
ompl::geometric::EST::MotionThe definition of a motion
ompl::geometric::EST::MotionInfoA struct containing an array of motions and a corresponding PDF element
ompl::geometric::EST::TreeDataThe data contained by a tree of exploration
ompl::geometric::FMTAsymptotically Optimal Fast Marching Tree algorithm developed by L. Janson and M. Pavone
ompl::geometric::FMT::MotionRepresentation of a motion
ompl::geometric::FMT::MotionCompareComparator used to order motions in a binary heap
ompl::geometric::GeneticSearchGenetic Algorithm for searching valid states
ompl::geometric::HillClimbingHill Climbing search
ompl::geometric::KBoundedStrategy< Milestone >Return at most k neighbors, as long as they are also within a specified bound
ompl::geometric::KPIECE1Kinematic Planning by Interior-Exterior Cell Exploration
ompl::geometric::KPIECE1::MotionRepresentation of a motion for this algorithm
ompl::geometric::KStarStrategy< Milestone >Make the minimal number of connections required to ensure asymptotic optimality
ompl::geometric::KStrategy< Milestone >
ompl::geometric::LazyPRMLazy Probabilistic RoadMap planner
ompl::geometric::LazyPRM::edge_flags_t
ompl::geometric::LazyPRM::vertex_component_t
ompl::geometric::LazyPRM::vertex_flags_t
ompl::geometric::LazyPRM::vertex_state_t
ompl::geometric::LazyPRMstarPRM* planner
ompl::geometric::LazyRRTLazy RRT
ompl::geometric::LazyRRT::MotionRepresentation of a motion
ompl::geometric::LBKPIECE1Lazy Bi-directional KPIECE with one level of discretization
ompl::geometric::LBKPIECE1::MotionRepresentation of a motion for this algorithm
ompl::geometric::LBTRRTLower Bound Tree Rapidly-exploring Random Trees
ompl::geometric::LBTRRT::CostCompare
ompl::geometric::LBTRRT::MotionRepresentation of a motion
ompl::geometric::PathGeometricDefinition of a geometric path
ompl::geometric::PathHybridizationGiven multiple geometric paths, attempt to combine them in order to obtain a shorter solution
ompl::geometric::PathHybridizationPtrA boost shared pointer wrapper for ompl::geometric::PathHybridization
ompl::geometric::PathSimplifierThis class contains routines that attempt to simplify geometric paths
ompl::geometric::PathSimplifierPtrA boost shared pointer wrapper for ompl::geometric::PathSimplifier
ompl::geometric::PDSTPath-Directed Subdivision Tree
ompl::geometric::PDST::CellCell is a Binary Space Partition
ompl::geometric::PDST::MotionClass representing the tree of motions exploring the state space
ompl::geometric::PDST::MotionCompareComparator used to order motions in the priority queue
ompl::geometric::PRMProbabilistic RoadMap planner
ompl::geometric::PRM::vertex_state_t
ompl::geometric::PRM::vertex_successful_connection_attempts_t
ompl::geometric::PRM::vertex_total_connection_attempts_t
ompl::geometric::PRMstarPRM* planner
ompl::geometric::pRRTParallel RRT
ompl::geometric::pRRT::Motion
ompl::geometric::pRRT::SolutionInfo
ompl::geometric::pSBLParallel Single-query Bi-directional Lazy collision checking planner
ompl::geometric::pSBL::Motion
ompl::geometric::pSBL::MotionInfoA struct containing an array of motions and a corresponding PDF element
ompl::geometric::pSBL::MotionsToBeRemoved
ompl::geometric::pSBL::PendingRemoveMotion
ompl::geometric::pSBL::SolutionInfo
ompl::geometric::pSBL::TreeData
ompl::geometric::RRTRapidly-exploring Random Trees
ompl::geometric::RRT::MotionRepresentation of a motion
ompl::geometric::RRTConnectRRT-Connect (RRTConnect)
ompl::geometric::RRTConnect::MotionRepresentation of a motion
ompl::geometric::RRTConnect::TreeGrowingInfoInformation attached to growing a tree of motions (used internally)
ompl::geometric::RRTstarOptimal Rapidly-exploring Random Trees
ompl::geometric::RRTstar::CostIndexCompare
ompl::geometric::RRTstar::MotionRepresentation of a motion
ompl::geometric::RRTstar::PruneScratchSpace
ompl::geometric::SBLSingle-Query Bi-Directional Probabilistic Roadmap Planner with Lazy Collision Checking
ompl::geometric::SBL::MotionRepresentation of a motion
ompl::geometric::SBL::MotionInfoA struct containing an array of motions and a corresponding PDF element
ompl::geometric::SBL::TreeDataRepresentation of a search tree. Two instances will be used. One for start and one for goal
ompl::geometric::SimpleSetupCreate the set of classes typically needed to solve a geometric problem
ompl::geometric::SimpleSetupPtrA boost shared pointer wrapper for ompl::geometric::SimpleSetup
ompl::geometric::SPARS SPArse Roadmap Spanner technique.
ompl::geometric::SPARS::InterfaceHashStruct
ompl::geometric::SPARS::vertex_color_t
ompl::geometric::SPARS::vertex_interface_list_t
ompl::geometric::SPARS::vertex_list_t
ompl::geometric::SPARS::vertex_representative_t
ompl::geometric::SPARS::vertex_state_t
ompl::geometric::SPARStwo SPArse Roadmap Spanner Version 2.0
ompl::geometric::SPARStwo::InterfaceDataInterface information storage class, which does bookkeeping for criterion four
ompl::geometric::SPARStwo::InterfaceHashStruct
ompl::geometric::SPARStwo::vertex_color_t
ompl::geometric::SPARStwo::vertex_interface_data_t
ompl::geometric::SPARStwo::vertex_state_t
ompl::geometric::STRIDESearch Tree with Resolution Independent Density Estimation
ompl::geometric::STRIDE::MotionThe definition of a motion
ompl::geometric::TRRTTransition-based Rapidly-exploring Random Trees
ompl::geometric::TRRT::MotionRepresentation of a motion
ompl::GreedyKCenters< _T >An instance of this class can be used to greedily select a given number of representatives from a set of data points that are all far apart from each other
ompl::Grid< _T >Representation of a simple grid
ompl::Grid< _T >::CellDefinition of a cell in this grid
ompl::Grid< _T >::EqualCoordPtrEquality operator for coordinate pointers
ompl::Grid< _T >::HashFunCoordPtrHash function for coordinates; see http://www.cs.hmc.edu/~geoff/classes/hmc.cs070.200101/homework10/hashfuncs.html
ompl::Grid< _T >::SortComponentsHelper to sort components by size
ompl::GridB< _T, LessThanExternal, LessThanInternal >This class defines a grid that keeps track of its boundary: it distinguishes between interior and exterior cells
ompl::GridB< _T, LessThanExternal, LessThanInternal >::LessThanExternalCellDefine order for external cells
ompl::GridB< _T, LessThanExternal, LessThanInternal >::LessThanInternalCellDefine order for internal cells
ompl::GridN< _T >Representation of a grid where cells keep track of how many neighbors they have
ompl::GridN< _T >::CellDefinition of a cell in this grid
ompl::msg::OutputHandlerGeneric class to handle output from a piece of code
ompl::msg::OutputHandlerFileImplementation of OutputHandler that saves messages in a file
ompl::msg::OutputHandlerSTDDefault implementation of OutputHandler. This sends the information to the console
ompl::NearestNeighbors< _T >Abstract representation of a container that can perform nearest neighbors queries
ompl::NearestNeighborsFLANN< _T, _Dist >Wrapper class for nearest neighbor data structures in the FLANN library
ompl::NearestNeighborsFLANNHierarchicalClustering< _T, _Dist >
ompl::NearestNeighborsFLANNLinear< _T, _Dist >
ompl::NearestNeighborsGNAT< _T >Geometric Near-neighbor Access Tree (GNAT), a data structure for nearest neighbor search
ompl::NearestNeighborsGNAT< _T >::NodeThe class used internally to define the GNAT
ompl::NearestNeighborsLinear< _T >A nearest neighbors datastructure that uses linear search
ompl::NearestNeighborsSqrtApprox< _T >A nearest neighbors datastructure that uses linear search. The linear search is done over sqrt(n) elements only. (Every sqrt(n) elements are skipped)
ompl::PDF< _T >A container that supports probabilistic sampling over weighted data
ompl::PDF< _T >::ElementA class that will hold data contained in the PDF
ompl::PPMLoad and save .ppm files
ompl::PPM::Color
ompl::RNGRandom number generation. An instance of this class cannot be used by multiple threads at once (member functions are not const). However, the constructor is thread safe and different instances can be used safely in any number of threads. It is also guaranteed that all created instances will have a different random seed
ompl::tools::BenchmarkBenchmark a set of planners on a problem instance
ompl::tools::Benchmark::CompleteExperimentThis structure holds experimental data for a set of planners
ompl::tools::Benchmark::PlannerExperimentThe data collected after running a planner multiple times
ompl::tools::Benchmark::RequestRepresentation of a benchmark request
ompl::tools::Benchmark::StatusThis structure contains information about the activity of a benchmark instance. If the instance is running, it is possible to find out information such as which planner is currently being tested or how much
ompl::tools::OptimizePlanRun one or more motion planners repeatedly (using a specified number of threads), and hybridize solutions, trying to optimize solutions
ompl::tools::ParallelPlanThis is a utility that allows executing multiple planners in parallel, until one or more find a solution. Optionally, the results are automatically hybridized using ompl::geometric::PathHybridization. Between calls to solve(), the set of known solutions (maintained by ompl::base::Goal) are not cleared, and neither is the hybridization datastructure
ompl::tools::PlannerMonitorMonitor the properties a planner exposes, as the planner is running. Dump the planner properties to a stream, periodically
ompl::tools::ProfilerThis is a simple thread-safe tool for counting time spent in various chunks of code. This is different from external profiling tools in that it allows the user to count time spent in various bits of code (sub-function granularity) or count how many times certain pieces of code are executed
ompl::tools::Profiler::ScopedBlockThis instance will call Profiler::begin() when constructed and Profiler::end() when it goes out of scope
ompl::tools::Profiler::ScopedStartThis instance will call Profiler::start() when constructed and Profiler::stop() when it goes out of scope. If the profiler was already started, this block's constructor and destructor take no action
ompl::tools::SelfConfigThis class contains methods that automatically configure various parameters for motion planning. If expensive computation is performed, the results are cached
Point2DPlanning.Plane2DEnvironment
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