ompl::control Namespace Reference

This namespace contains sampling based planning routines used by planning under differential constraints. More...

## Classes | |

class | Automaton |

A 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. More... | |

class | CompoundControl |

Definition of a compound control. More... | |

class | CompoundControlSampler |

Definition of a compound control sampler. This is useful to construct samplers for compound controls. More... | |

class | CompoundControlSpace |

A control space to allow the composition of control spaces. More... | |

class | Control |

Definition of an abstract control. More... | |

class | ControlSampler |

Abstract 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. More... | |

class | ControlSpace |

A control space representing the space of applicable controls. More... | |

class | Decomposition |

A Decomposition is a partition of a bounded Euclidean space into a fixed number of regions which are denoted by integers. More... | |

class | DirectedControlSampler |

Abstract 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. More... | |

class | DiscreteControlSampler |

Control space sampler for discrete controls. More... | |

class | DiscreteControlSpace |

A 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. More... | |

class | EST |

Expansive Space Trees. More... | |

class | GridDecomposition |

A GridDecomposition is a Decomposition implemented using a grid. More... | |

class | KPIECE1 |

Kinodynamic Planning by Interior-Exterior Cell Exploration. More... | |

class | LTLPlanner |

A 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. More... | |

class | LTLProblemDefinition |

class | LTLSpaceInformation |

class | MorseControlSpace |

Representation of controls applied in MORSE environments. This is an array of double values. More... | |

class | MorseSimpleSetup |

Create the set of classes typically needed to solve a control problem when forward propagation is computed with MORSE. More... | |

class | MorseStatePropagator |

State propagation with MORSE. Only forward propagation is possible. More... | |

class | ODEAdaptiveSolver |

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. More... | |

class | ODEBasicSolver |

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. More... | |

class | ODEErrorSolver |

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. More... | |

class | ODESolver |

Abstract 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. More... | |

class | OpenDEControlSpace |

Representation of controls applied in OpenDE environments. This is an array of double values. More... | |

class | OpenDEEnvironment |

This class contains the OpenDE constructs OMPL needs to know about when planning. More... | |

class | OpenDESimpleSetup |

Create the set of classes typically needed to solve a control problem when forward propagation is computed with OpenDE. More... | |

class | OpenDEStatePropagator |

State propagation with OpenDE. Only forward propagation is possible. More... | |

class | OpenDEStateSpace |

State space representing OpenDE states. More... | |

class | OpenDEStateValidityChecker |

The simplest state validity checker: all states are valid. More... | |

class | PathControl |

Definition of a control path. More... | |

class | PDST |

Path-Directed Subdivision Tree. More... | |

class | PlannerData |

Object containing planner generated vertex and edge data. It is assumed that all vertices are unique, and only a single directed edge connects two vertices. More... | |

class | PlannerDataEdgeControl |

Representation of an edge in PlannerData for planning with controls. This structure encodes a specific control and a duration to apply the control. More... | |

class | PlannerDataStorage |

Object 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. More... | |

class | ProductGraph |

A 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. More... | |

class | PropositionalDecomposition |

A propositional decomposition wraps a given Decomposition with a region-to-proposition assignment operator. Each region in the decomposition has a corresponding World. More... | |

class | PropositionalTriangularDecomposition |

A 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. More... | |

class | RealVectorControlSpace |

A control space representing R^{n}. More... | |

class | RealVectorControlUniformSampler |

Uniform sampler for the R^{n} state space. More... | |

class | RRT |

Rapidly-exploring Random Tree. More... | |

class | SimpleDirectedControlSampler |

Implementation 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. More... | |

class | SimpleSetup |

Create the set of classes typically needed to solve a control problem. More... | |

class | SpaceInformation |

Space information containing necessary information for planning with controls. setup() needs to be called before use. More... | |

class | SST |

class | StatePropagator |

Model the effect of controls on system states. More... | |

class | SteeredControlSampler |

Abstract 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. More... | |

class | Syclop |

Synergistic Combination of Layers of Planning. More... | |

class | SyclopEST |

SyclopEST is Syclop with EST as its low-level tree planner. More... | |

class | SyclopRRT |

SyclopRRT is Syclop with RRT as its low-level tree planner. More... | |

class | TriangularDecomposition |

A TriangularDecomposition is a triangulation that ignores obstacles. More... | |

class | World |

A 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. More... | |

## Typedefs | |

using | ControlSamplerAllocator = std::function< ControlSamplerPtr(const ControlSpace *)> |

Definition of a function that can allocate a control sampler. | |

using | DirectedControlSamplerAllocator = std::function< DirectedControlSamplerPtr(const SpaceInformation *)> |

Definition of a function that can allocate a directed control sampler. | |

using | StatePropagatorFn = std::function< void(const base::State *, const Control *, const double, base::State *)> |

A function that achieves state propagation. | |

## Enumerations | |

enum | ControlSpaceType { CONTROL_SPACE_UNKNOWN = 0, CONTROL_SPACE_REAL_VECTOR = 1, CONTROL_SPACE_DISCRETE = 2, CONTROL_SPACE_TYPE_COUNT } |

The type of a control space. More... | |

## Functions | |

std::ostream & | operator<< (std::ostream &out, const ProductGraph::State &s) |

OMPL_DEPRECATED base::PlannerPtr | getDefaultPlanner (const base::GoalPtr &goal) |

Given a goal specification, decide on a planner for that goal. More... | |

## Detailed Description

This namespace contains sampling based planning routines used by planning under differential constraints.

## Enumeration Type Documentation

## ◆ ControlSpaceType

The type of a control space.

Definition at line 106 of file ControlSpaceTypes.h.

## Function Documentation

## ◆ getDefaultPlanner()

ompl::base::PlannerPtr ompl::control::getDefaultPlanner | ( | const base::GoalPtr & | goal | ) |

Given a goal specification, decide on a planner for that goal.

**Deprecated:**- Use tools::SelfConfig::getDefaultPlanner() instead.

Definition at line 39 of file SimpleSetup.cpp.