Available Variables/Factors

Variables in Caesar.jl

You can check for the latest variable types by running the following in your terminal:

using RoME, Caesar
subtypes(IncrementalInference.InferenceVariable)
IncrementalInference.getCurrentWorkspaceVariables()

Default variables in IncrementalInference

struct ContinuousScalar <: InferenceVariable

Most basic continuous scalar variable a ::FactorGraph object.

struct ContinuousMultivariate{T1<:Tuple} <: InferenceVariable

Continuous variable of dimension .dims on manifold .manifolds.

2D Variables

The current variables types are:

Missing docstring.

Missing docstring for Polar. Check Documenter's build log for details.

RoME.Point2Type.
struct Point2 <: InferenceVariable

XY Euclidean manifold variable node softtype.

RoME.Pose2Type.
struct Pose2 <: InferenceVariable

Pose2 is a SE(2) mechanization of two Euclidean translations and one Circular rotation, used for general 2D SLAM.

RoME.DynPoint2Type.
mutable struct DynPoint2 <: InferenceVariable

Dynamic point in 2D space with velocity components: x, y, dx/dt, dy/dt

RoME.DynPose2Type.
mutable struct DynPose2 <: InferenceVariable

Dynamic pose variable with velocity components: x, y, theta, dx/dt, dy/dt

3D Variables

RoME.Point3Type.
struct Point3 <: InferenceVariable

XYZ Euclidean manifold variable node softtype.

Example

p3 = Point3()
RoME.Pose3Type.
struct Pose3 <: InferenceVariable

Pose3 is currently a Euler angle mechanization of three Euclidean translations and three Circular rotation.

Future:

  • Work in progress on AMP3D for proper non-Euler angle on-manifold operations.
mutable struct InertialPose3 <: FunctorPairwise

Inertial Odometry version of preintegration procedure and used as a factor between InertialPose3 types for inertial navigation in factor graphs.

Note Please open an issue with JuliaRobotics/RoME.jl for specific requests, problems, or suggestions. Contributions are also welcome.

Note There might be more variable types in Caesar/RoME/IIF not yet documented here.

Factors in Caesar.jl

You can check for the latest factor types by running the following in your terminal:

using RoME, Caesar
println("- Singletons (priors): ")
println.(sort(string.(subtypes(IncrementalInference.FunctorSingleton))));
println("- Pairwise (variable constraints): ")
println.(sort(string.(subtypes(IncrementalInference.FunctorPairwise))));
println("- Pairwise (variable minimization constraints): ")
println.(sort(string.(subtypes(IncrementalInference.FunctorPairwiseMinimize))));

Priors (Absolute Data)

Existing prior (unary) factors in Caesar.jl/RoME.jl/IIF.jl include:

RoME.PriorPolarType.
mutable struct PriorPolar{T1<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorSingleton

Prior belief on any Polar related variable.

mutable struct PriorPoint2{T} <: FunctorSingleton

Direction observation information of a Point2 variable.

RoME.PriorPose2Type.
mutable struct PriorPose2{T} <: FunctorSingleton

Introduce direct observations on all dimensions of a Pose2 variable:

Example:

PriorPose2( MvNormal([10; 10; pi/6.0], Matrix(Diagonal([0.1;0.1;0.05].^2))) )

Prior 3D (unary) factors

mutable struct PriorPoint3{T} <: FunctorSingleton

Direction observation information of a Point3 variable.

RoME.PriorPose3Type.
mutable struct PriorPose3 <: FunctorSingleton

Direct observation information of Pose3 variable type.

Defaults in IncrementalInference.jl:

struct Prior{T} <: FunctorSingleton

Default prior on all dimensions of a variable node in the factor graph. Prior is not recommended when non-Euclidean dimensions are used in variables.

struct PartialPrior{T, P} <: FunctorSingleton

Partial prior belief (absolute data) on any variable, given <:SamplableBelief and which dimensions of the intended variable.

struct MixturePrior{T} <: FunctorSingleton

Define a categorical mixture of prior beliefs on a variable.

Conditional Likelihoods (Relative Data)

Existing n-ary factors in Caesar.jl/RoME.jl/IIF.jl include:

RoME.PolarPolarType.
mutable struct PolarPolar{T1<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}, T2<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwise

Linear offset factor of IIF.SamplableBelief between two Polar variables.

mutable struct Point2Point2{D<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwise
mutable struct Point2Point2WorldBearing{T} <: FunctorPairwise
mutable struct Pose2Point2Bearing{B<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwiseMinimize

Single dimension bearing constraint from Pose2 to Point2 variable.

mutable struct Pose2Point2BearingRange{B<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}, R<:Union{AliasingScalarSampler, BallTreeDensity, Distribution}} <: FunctorPairwiseMinimize

Bearing and Range constraint from a Pose2 to Point2 variable.

mutable struct Pose2Point2Range{T} <: FunctorPairwise

Range only measurement from Pose2 to Point2 variable.

RoME.Pose2Pose2Type.
mutable struct Pose2Pose2{T} <: FunctorPairwise
mutable struct DynPoint2VelocityPrior{T} <: FunctorSingleton
mutable struct DynPoint2DynPoint2{T} <: FunctorPairwise
mutable struct VelPoint2VelPoint2{T} <: FunctorPairwiseMinimize
mutable struct Point2Point2Velocity{T} <: FunctorPairwiseMinimize
mutable struct DynPose2VelocityPrior{T1, T2} <: FunctorSingleton
mutable struct VelPose2VelPose2{T1, T2} <: FunctorPairwiseMinimize
mutable struct DynPose2Pose2{T} <: FunctorPairwise
RoME.Pose3Pose3Type.
mutable struct Pose3Pose3 <: FunctorPairwise

Rigid transform factor between two Pose3 compliant variables.

Missing docstring.

Missing docstring for InertialPose3. Check Documenter's build log for details.

mutable struct PriorPose3ZRP{T1, T2} <: FunctorSingleton

Partial prior belief on Z, Roll, and Pitch of a Pose3.

mutable struct PartialPriorRollPitchZ{T1, T2} <: FunctorSingleton

Partial prior belief on Roll Pitch and Z of a Pose3 variable.

mutable struct PartialPose3XYYaw{T1, T2} <: FunctorPairwise

Partial factor between XY and Yaw of two Pose3 variables.

To be deprecated: use Pose3Pose3XYYaw instead.

mutable struct Pose3Pose3XYYaw{T1, T2} <: FunctorPairwise

Partial factor between XY and Yaw of two Pose3 variables.

Defaults in IncrementalInference.jl:

struct LinearConditional{T} <: FunctorPairwise

Default linear offset between two scalar variables.

struct MixtureLinearConditional{T} <: FunctorPairwise

Define a categorical mixture of (relative) likelihood beliefs between any two variables.

Extending Caesar with New Variables and Factors

A question that frequently arises is how to design custom variables and factors to solve a specific type of graph. One strength of Caesar is the ability to incorporate new variables and factors at will. Please refer to Adding Factors for more information on creating your own factors.